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index a3a67396b1..7a4cba3e5b 100644
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index 4430df5dcc..b2964e9f37 100644
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index 99d1ccda90..23f127343d 100644
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index c10793b4d2..606926fdeb 100644
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index 2b124d73b5..ef78997fe9 100644
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index 35859a3ae8..336ae5522c 100644
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index 83b82b308a..96bcad5987 100644
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index c95d179335..5cafbcf25d 100644
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index 926a652f64..286b843ff4 100644
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index 3823f941fb..fe0edab8da 100644
--- a/autosklearn/experimental/log_loss/askl2_portfolios/RF_SH-eta4-i_holdout_iterative_es_if.json
+++ b/autosklearn/experimental/log_loss/askl2_portfolios/RF_SH-eta4-i_holdout_iterative_es_if.json
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index 28cf8bc1cd..a270e86217 100644
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index a26e4ec237..db7cd35f5c 100644
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index 29c92e1ae2..882b8c6c2c 100644
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index d5dc0fefb1..12c6cf2e01 100644
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index 42df526afa..d99c235d16 100644
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index fc060cb7f3..6bcc253cfd 100644
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diff --git a/autosklearn/metalearning/files/accuracy_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/accuracy_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/accuracy_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/accuracy_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/accuracy_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/accuracy_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/accuracy_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/accuracy_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/accuracy_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/accuracy_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/accuracy_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/accuracy_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/accuracy_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/accuracy_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/accuracy_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/accuracy_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/average_precision_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/average_precision_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 27e7f845c0..29ee07ac6b
--- a/autosklearn/metalearning/files/average_precision_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/average_precision_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/average_precision_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/average_precision_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 13913cc700..fc766d5cf9
--- a/autosklearn/metalearning/files/average_precision_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/average_precision_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/average_precision_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/average_precision_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 27e7f845c0..29ee07ac6b
--- a/autosklearn/metalearning/files/average_precision_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/average_precision_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/average_precision_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/average_precision_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 13913cc700..fc766d5cf9
--- a/autosklearn/metalearning/files/average_precision_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/average_precision_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/balanced_accuracy_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/balanced_accuracy_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 60317e43fa..e890697816
--- a/autosklearn/metalearning/files/balanced_accuracy_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/balanced_accuracy_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/balanced_accuracy_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/balanced_accuracy_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index bc41a22578..1a24c2d595
--- a/autosklearn/metalearning/files/balanced_accuracy_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/balanced_accuracy_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 60317e43fa..e890697816
--- a/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index bc41a22578..1a24c2d595
--- a/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/balanced_accuracy_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 8449f8febc..676a1df63e
--- a/autosklearn/metalearning/files/f1_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 91842e6a15..1f774bef61
--- a/autosklearn/metalearning/files/f1_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_macro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_macro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 3925fec717..e9f06dacb9
--- a/autosklearn/metalearning/files/f1_macro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_macro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_macro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_macro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index e74f023219..ca19669f40
--- a/autosklearn/metalearning/files/f1_macro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_macro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_macro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_macro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 3925fec717..e9f06dacb9
--- a/autosklearn/metalearning/files/f1_macro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_macro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_macro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_macro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index e74f023219..ca19669f40
--- a/autosklearn/metalearning/files/f1_macro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_macro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_micro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_micro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/f1_micro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_micro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_micro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_micro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/f1_micro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_micro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_micro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_micro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/f1_micro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_micro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_micro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_micro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/f1_micro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_micro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 8449f8febc..676a1df63e
--- a/autosklearn/metalearning/files/f1_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 91842e6a15..1f774bef61
--- a/autosklearn/metalearning/files/f1_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_samples_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_samples_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/f1_samples_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_samples_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_samples_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_samples_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/f1_samples_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_samples_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_samples_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_samples_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/f1_samples_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_samples_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_samples_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_samples_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/f1_samples_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_samples_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_weighted_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_weighted_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 77b926a09e..8e6e90e03b
--- a/autosklearn/metalearning/files/f1_weighted_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_weighted_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_weighted_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_weighted_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 6abcc4c1a7..8d863e48ba
--- a/autosklearn/metalearning/files/f1_weighted_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_weighted_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_weighted_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/f1_weighted_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 77b926a09e..8e6e90e03b
--- a/autosklearn/metalearning/files/f1_weighted_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/f1_weighted_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/f1_weighted_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/f1_weighted_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 6abcc4c1a7..8d863e48ba
--- a/autosklearn/metalearning/files/f1_weighted_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/f1_weighted_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/log_loss_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/log_loss_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index ee4c4899ce..98509d0f5b
--- a/autosklearn/metalearning/files/log_loss_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/log_loss_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/log_loss_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/log_loss_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index ced6b2928b..c35bee51de
--- a/autosklearn/metalearning/files/log_loss_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/log_loss_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/log_loss_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/log_loss_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index ee4c4899ce..98509d0f5b
--- a/autosklearn/metalearning/files/log_loss_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/log_loss_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/log_loss_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/log_loss_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index ced6b2928b..c35bee51de
--- a/autosklearn/metalearning/files/log_loss_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/log_loss_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_absolute_error_regression_dense/configurations.csv b/autosklearn/metalearning/files/mean_absolute_error_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 4e22396df7..cd3ed0fbc6
--- a/autosklearn/metalearning/files/mean_absolute_error_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/mean_absolute_error_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_absolute_error_regression_sparse/configurations.csv b/autosklearn/metalearning/files/mean_absolute_error_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 4e22396df7..cd3ed0fbc6
--- a/autosklearn/metalearning/files/mean_absolute_error_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/mean_absolute_error_regression_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_squared_error_regression_dense/configurations.csv b/autosklearn/metalearning/files/mean_squared_error_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/mean_squared_error_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/mean_squared_error_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_squared_error_regression_sparse/configurations.csv b/autosklearn/metalearning/files/mean_squared_error_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/mean_squared_error_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/mean_squared_error_regression_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_squared_log_error_regression_dense/configurations.csv b/autosklearn/metalearning/files/mean_squared_log_error_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 59a35b5748..973d29e000
--- a/autosklearn/metalearning/files/mean_squared_log_error_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/mean_squared_log_error_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/mean_squared_log_error_regression_sparse/configurations.csv b/autosklearn/metalearning/files/mean_squared_log_error_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 59a35b5748..973d29e000
--- a/autosklearn/metalearning/files/mean_squared_log_error_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/mean_squared_log_error_regression_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/median_absolute_error_regression_dense/configurations.csv b/autosklearn/metalearning/files/median_absolute_error_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 8948f7b271..3c49c2bf6f
--- a/autosklearn/metalearning/files/median_absolute_error_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/median_absolute_error_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/median_absolute_error_regression_sparse/configurations.csv b/autosklearn/metalearning/files/median_absolute_error_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 8948f7b271..3c49c2bf6f
--- a/autosklearn/metalearning/files/median_absolute_error_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/median_absolute_error_regression_sparse/configurations.csv
@@ -1,4 +1,4 @@
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diff --git a/autosklearn/metalearning/files/precision_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 3334ad1e0d..c79fe1417b
--- a/autosklearn/metalearning/files/precision_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_binary.classification_dense/configurations.csv
@@ -1,4 +1,4 @@
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diff --git a/autosklearn/metalearning/files/precision_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index eb7eb7fffe..781dfab9bc
--- a/autosklearn/metalearning/files/precision_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_macro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_macro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 078d16ac48..b4facfc6dc
--- a/autosklearn/metalearning/files/precision_macro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_macro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_macro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_macro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 3f31b0ee8f..f74616704f
--- a/autosklearn/metalearning/files/precision_macro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_macro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_macro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_macro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 078d16ac48..b4facfc6dc
--- a/autosklearn/metalearning/files/precision_macro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_macro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_macro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_macro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 3f31b0ee8f..f74616704f
--- a/autosklearn/metalearning/files/precision_macro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_macro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_micro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_micro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/precision_micro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_micro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_micro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_micro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/precision_micro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_micro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_micro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_micro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/precision_micro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_micro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_micro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_micro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/precision_micro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_micro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 3334ad1e0d..c79fe1417b
--- a/autosklearn/metalearning/files/precision_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index eb7eb7fffe..781dfab9bc
--- a/autosklearn/metalearning/files/precision_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_samples_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_samples_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/precision_samples_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_samples_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_samples_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_samples_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/precision_samples_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_samples_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_samples_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_samples_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/precision_samples_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_samples_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_samples_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_samples_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/precision_samples_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_samples_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_weighted_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_weighted_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 8f0ae5290a..e9537b0d7e
--- a/autosklearn/metalearning/files/precision_weighted_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_weighted_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_weighted_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_weighted_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 5d60cc6a60..786e3f901f
--- a/autosklearn/metalearning/files/precision_weighted_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_weighted_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_weighted_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/precision_weighted_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 8f0ae5290a..e9537b0d7e
--- a/autosklearn/metalearning/files/precision_weighted_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/precision_weighted_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/precision_weighted_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/precision_weighted_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 5d60cc6a60..786e3f901f
--- a/autosklearn/metalearning/files/precision_weighted_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/precision_weighted_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/r2_regression_dense/configurations.csv b/autosklearn/metalearning/files/r2_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/r2_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/r2_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/r2_regression_sparse/configurations.csv b/autosklearn/metalearning/files/r2_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/r2_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/r2_regression_sparse/configurations.csv
@@ -1,4 +1,4 @@
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diff --git a/autosklearn/metalearning/files/recall_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 645e0b2ebe..16be8c5402
--- a/autosklearn/metalearning/files/recall_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_binary.classification_dense/configurations.csv
@@ -1,4 +1,4 @@
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diff --git a/autosklearn/metalearning/files/recall_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 1f3d8fe63f..052709a74c
--- a/autosklearn/metalearning/files/recall_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_macro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_macro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index e445d1fd5d..39de07a0b2
--- a/autosklearn/metalearning/files/recall_macro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_macro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_macro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_macro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index bc41a22578..1a24c2d595
--- a/autosklearn/metalearning/files/recall_macro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_macro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_macro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_macro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index e445d1fd5d..39de07a0b2
--- a/autosklearn/metalearning/files/recall_macro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_macro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_macro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_macro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index bc41a22578..1a24c2d595
--- a/autosklearn/metalearning/files/recall_macro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_macro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_micro_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_micro_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/recall_micro_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_micro_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_micro_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_micro_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/recall_micro_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_micro_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_micro_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_micro_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/recall_micro_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_micro_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_micro_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_micro_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/recall_micro_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_micro_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 645e0b2ebe..16be8c5402
--- a/autosklearn/metalearning/files/recall_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 1f3d8fe63f..052709a74c
--- a/autosklearn/metalearning/files/recall_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_samples_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_samples_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/recall_samples_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_samples_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_samples_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_samples_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/recall_samples_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_samples_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_samples_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_samples_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index edb747b9ab..0fdecb010d
--- a/autosklearn/metalearning/files/recall_samples_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_samples_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_samples_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_samples_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 116a116b94..e3239fc39c
--- a/autosklearn/metalearning/files/recall_samples_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_samples_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_weighted_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_weighted_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/recall_weighted_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_weighted_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_weighted_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_weighted_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/recall_weighted_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_weighted_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_weighted_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/recall_weighted_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index c4c3c3ca95..dc72828c02
--- a/autosklearn/metalearning/files/recall_weighted_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/recall_weighted_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/recall_weighted_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/recall_weighted_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index dab35693c2..7f37f740d2
--- a/autosklearn/metalearning/files/recall_weighted_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/recall_weighted_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/roc_auc_binary.classification_dense/configurations.csv b/autosklearn/metalearning/files/roc_auc_binary.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 10a4a9a1f6..a5c27c2f85
--- a/autosklearn/metalearning/files/roc_auc_binary.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/roc_auc_binary.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/roc_auc_binary.classification_sparse/configurations.csv b/autosklearn/metalearning/files/roc_auc_binary.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 910972f98a..5c9bbcd799
--- a/autosklearn/metalearning/files/roc_auc_binary.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/roc_auc_binary.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/roc_auc_multiclass.classification_dense/configurations.csv b/autosklearn/metalearning/files/roc_auc_multiclass.classification_dense/configurations.csv
old mode 100755
new mode 100644
index 10a4a9a1f6..a5c27c2f85
--- a/autosklearn/metalearning/files/roc_auc_multiclass.classification_dense/configurations.csv
+++ b/autosklearn/metalearning/files/roc_auc_multiclass.classification_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/roc_auc_multiclass.classification_sparse/configurations.csv b/autosklearn/metalearning/files/roc_auc_multiclass.classification_sparse/configurations.csv
old mode 100755
new mode 100644
index 910972f98a..5c9bbcd799
--- a/autosklearn/metalearning/files/roc_auc_multiclass.classification_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/roc_auc_multiclass.classification_sparse/configurations.csv
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diff --git a/autosklearn/metalearning/files/root_mean_squared_error_regression_dense/configurations.csv b/autosklearn/metalearning/files/root_mean_squared_error_regression_dense/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/root_mean_squared_error_regression_dense/configurations.csv
+++ b/autosklearn/metalearning/files/root_mean_squared_error_regression_dense/configurations.csv
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diff --git a/autosklearn/metalearning/files/root_mean_squared_error_regression_sparse/configurations.csv b/autosklearn/metalearning/files/root_mean_squared_error_regression_sparse/configurations.csv
old mode 100755
new mode 100644
index 7f036f16fc..9dc0c52684
--- a/autosklearn/metalearning/files/root_mean_squared_error_regression_sparse/configurations.csv
+++ b/autosklearn/metalearning/files/root_mean_squared_error_regression_sparse/configurations.csv
@@ -1,4 +1,4 @@
-idx,data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction,data_preprocessor:feature_type:numerical_transformer:imputation:strategy,data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:n_quantiles,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:output_distribution,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_max,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_min,feature_preprocessor:__choice__,feature_preprocessor:extra_trees_preproc_for_regression:bootstrap,feature_preprocessor:extra_trees_preproc_for_regression:criterion,feature_preprocessor:extra_trees_preproc_for_regression:max_depth,feature_preprocessor:extra_trees_preproc_for_regression:max_features,feature_preprocessor:extra_trees_preproc_for_regression:max_leaf_nodes,feature_preprocessor:extra_trees_preproc_for_regression:min_samples_leaf,feature_preprocessor:extra_trees_preproc_for_regression:min_samples_split,feature_preprocessor:extra_trees_preproc_for_regression:min_weight_fraction_leaf,feature_preprocessor:extra_trees_preproc_for_regression:n_estimators,feature_preprocessor:fast_ica:algorithm,feature_preprocessor:fast_ica:fun,feature_preprocessor:fast_ica:n_components,feature_preprocessor:fast_ica:whiten,feature_preprocessor:feature_agglomeration:affinity,feature_preprocessor:feature_agglomeration:linkage,feature_preprocessor:feature_agglomeration:n_clusters,feature_preprocessor:feature_agglomeration:pooling_func,feature_preprocessor:kernel_pca:coef0,feature_preprocessor:kernel_pca:degree,feature_preprocessor:kernel_pca:gamma,feature_preprocessor:kernel_pca:kernel,feature_preprocessor:kernel_pca:n_components,feature_preprocessor:kitchen_sinks:gamma,feature_preprocessor:kitchen_sinks:n_components,feature_preprocessor:nystroem_sampler:coef0,feature_preprocessor:nystroem_sampler:degree,feature_preprocessor:nystroem_sampler:gamma,feature_preprocessor:nystroem_sampler:kernel,feature_preprocessor:nystroem_sampler:n_components,feature_preprocessor:pca:keep_variance,feature_preprocessor:pca:whiten,feature_preprocessor:polynomial:degree,feature_preprocessor:polynomial:include_bias,feature_preprocessor:polynomial:interaction_only,feature_preprocessor:random_trees_embedding:bootstrap,feature_preprocessor:random_trees_embedding:max_depth,feature_preprocessor:random_trees_embedding:max_leaf_nodes,feature_preprocessor:random_trees_embedding:min_samples_leaf,feature_preprocessor:random_trees_embedding:min_samples_split,feature_preprocessor:random_trees_embedding:min_weight_fraction_leaf,feature_preprocessor:random_trees_embedding:n_estimators,feature_preprocessor:select_percentile_regression:percentile,feature_preprocessor:select_percentile_regression:score_func,feature_preprocessor:select_rates_regression:alpha,feature_preprocessor:select_rates_regression:mode,feature_preprocessor:select_rates_regression:score_func,regressor:__choice__,regressor:adaboost:learning_rate,regressor:adaboost:loss,regressor:adaboost:max_depth,regressor:adaboost:n_estimators,regressor:ard_regression:alpha_1,regressor:ard_regression:alpha_2,regressor:ard_regression:fit_intercept,regressor:ard_regression:lambda_1,regressor:ard_regression:lambda_2,regressor:ard_regression:n_iter,regressor:ard_regression:threshold_lambda,regressor:ard_regression:tol,regressor:decision_tree:criterion,regressor:decision_tree:max_depth_factor,regressor:decision_tree:max_features,regressor:decision_tree:max_leaf_nodes,regressor:decision_tree:min_impurity_decrease,regressor:decision_tree:min_samples_leaf,regressor:decision_tree:min_samples_split,regressor:decision_tree:min_weight_fraction_leaf,regressor:extra_trees:bootstrap,regressor:extra_trees:criterion,regressor:extra_trees:max_depth,regressor:extra_trees:max_features,regressor:extra_trees:max_leaf_nodes,regressor:extra_trees:min_impurity_decrease,regressor:extra_trees:min_samples_leaf,regressor:extra_trees:min_samples_split,regressor:extra_trees:min_weight_fraction_leaf,regressor:gaussian_process:alpha,regressor:gaussian_process:thetaL,regressor:gaussian_process:thetaU,regressor:gradient_boosting:early_stop,regressor:gradient_boosting:l2_regularization,regressor:gradient_boosting:learning_rate,regressor:gradient_boosting:loss,regressor:gradient_boosting:max_bins,regressor:gradient_boosting:max_depth,regressor:gradient_boosting:max_leaf_nodes,regressor:gradient_boosting:min_samples_leaf,regressor:gradient_boosting:n_iter_no_change,regressor:gradient_boosting:scoring,regressor:gradient_boosting:tol,regressor:gradient_boosting:validation_fraction,regressor:k_nearest_neighbors:n_neighbors,regressor:k_nearest_neighbors:p,regressor:k_nearest_neighbors:weights,regressor:liblinear_svr:C,regressor:liblinear_svr:dual,regressor:liblinear_svr:epsilon,regressor:liblinear_svr:fit_intercept,regressor:liblinear_svr:intercept_scaling,regressor:liblinear_svr:loss,regressor:liblinear_svr:tol,regressor:libsvm_svr:C,regressor:libsvm_svr:coef0,regressor:libsvm_svr:degree,regressor:libsvm_svr:epsilon,regressor:libsvm_svr:gamma,regressor:libsvm_svr:kernel,regressor:libsvm_svr:max_iter,regressor:libsvm_svr:shrinking,regressor:libsvm_svr:tol,regressor:mlp:activation,regressor:mlp:alpha,regressor:mlp:batch_size,regressor:mlp:beta_1,regressor:mlp:beta_2,regressor:mlp:early_stopping,regressor:mlp:epsilon,regressor:mlp:hidden_layer_depth,regressor:mlp:learning_rate_init,regressor:mlp:n_iter_no_change,regressor:mlp:num_nodes_per_layer,regressor:mlp:shuffle,regressor:mlp:solver,regressor:mlp:tol,regressor:mlp:validation_fraction,regressor:random_forest:bootstrap,regressor:random_forest:criterion,regressor:random_forest:max_depth,regressor:random_forest:max_features,regressor:random_forest:max_leaf_nodes,regressor:random_forest:min_impurity_decrease,regressor:random_forest:min_samples_leaf,regressor:random_forest:min_samples_split,regressor:random_forest:min_weight_fraction_leaf,regressor:sgd:alpha,regressor:sgd:average,regressor:sgd:epsilon,regressor:sgd:eta0,regressor:sgd:fit_intercept,regressor:sgd:l1_ratio,regressor:sgd:learning_rate,regressor:sgd:loss,regressor:sgd:penalty,regressor:sgd:power_t,regressor:sgd:tol,data_preprocessor:__choice__,data_preprocessor:feature_type:text_transformer:feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:__choice__,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:use_idf,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:ngram_range
+idx,data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction,data_preprocessor:feature_type:numerical_transformer:imputation:strategy,data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:n_quantiles,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:output_distribution,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_max,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_min,feature_preprocessor:__choice__,feature_preprocessor:extra_trees_preproc_for_regression:bootstrap,feature_preprocessor:extra_trees_preproc_for_regression:criterion,feature_preprocessor:extra_trees_preproc_for_regression:max_depth,feature_preprocessor:extra_trees_preproc_for_regression:max_features,feature_preprocessor:extra_trees_preproc_for_regression:max_leaf_nodes,feature_preprocessor:extra_trees_preproc_for_regression:min_samples_leaf,feature_preprocessor:extra_trees_preproc_for_regression:min_samples_split,feature_preprocessor:extra_trees_preproc_for_regression:min_weight_fraction_leaf,feature_preprocessor:extra_trees_preproc_for_regression:n_estimators,feature_preprocessor:fast_ica:algorithm,feature_preprocessor:fast_ica:fun,feature_preprocessor:fast_ica:n_components,feature_preprocessor:fast_ica:whiten,feature_preprocessor:feature_agglomeration:affinity,feature_preprocessor:feature_agglomeration:linkage,feature_preprocessor:feature_agglomeration:n_clusters,feature_preprocessor:feature_agglomeration:pooling_func,feature_preprocessor:kernel_pca:coef0,feature_preprocessor:kernel_pca:degree,feature_preprocessor:kernel_pca:gamma,feature_preprocessor:kernel_pca:kernel,feature_preprocessor:kernel_pca:n_components,feature_preprocessor:kitchen_sinks:gamma,feature_preprocessor:kitchen_sinks:n_components,feature_preprocessor:nystroem_sampler:coef0,feature_preprocessor:nystroem_sampler:degree,feature_preprocessor:nystroem_sampler:gamma,feature_preprocessor:nystroem_sampler:kernel,feature_preprocessor:nystroem_sampler:n_components,feature_preprocessor:pca:keep_variance,feature_preprocessor:pca:whiten,feature_preprocessor:polynomial:degree,feature_preprocessor:polynomial:include_bias,feature_preprocessor:polynomial:interaction_only,feature_preprocessor:random_trees_embedding:bootstrap,feature_preprocessor:random_trees_embedding:max_depth,feature_preprocessor:random_trees_embedding:max_leaf_nodes,feature_preprocessor:random_trees_embedding:min_samples_leaf,feature_preprocessor:random_trees_embedding:min_samples_split,feature_preprocessor:random_trees_embedding:min_weight_fraction_leaf,feature_preprocessor:random_trees_embedding:n_estimators,feature_preprocessor:select_percentile_regression:percentile,feature_preprocessor:select_percentile_regression:score_func,feature_preprocessor:select_rates_regression:alpha,feature_preprocessor:select_rates_regression:mode,feature_preprocessor:select_rates_regression:score_func,regressor:__choice__,regressor:adaboost:learning_rate,regressor:adaboost:loss,regressor:adaboost:max_depth,regressor:adaboost:n_estimators,regressor:ard_regression:alpha_1,regressor:ard_regression:alpha_2,regressor:ard_regression:fit_intercept,regressor:ard_regression:lambda_1,regressor:ard_regression:lambda_2,regressor:ard_regression:n_iter,regressor:ard_regression:threshold_lambda,regressor:ard_regression:tol,regressor:decision_tree:criterion,regressor:decision_tree:max_depth_factor,regressor:decision_tree:max_features,regressor:decision_tree:max_leaf_nodes,regressor:decision_tree:min_impurity_decrease,regressor:decision_tree:min_samples_leaf,regressor:decision_tree:min_samples_split,regressor:decision_tree:min_weight_fraction_leaf,regressor:extra_trees:bootstrap,regressor:extra_trees:criterion,regressor:extra_trees:max_depth,regressor:extra_trees:max_features,regressor:extra_trees:max_leaf_nodes,regressor:extra_trees:min_impurity_decrease,regressor:extra_trees:min_samples_leaf,regressor:extra_trees:min_samples_split,regressor:extra_trees:min_weight_fraction_leaf,regressor:gaussian_process:alpha,regressor:gaussian_process:thetaL,regressor:gaussian_process:thetaU,regressor:gradient_boosting:early_stop,regressor:gradient_boosting:l2_regularization,regressor:gradient_boosting:learning_rate,regressor:gradient_boosting:loss,regressor:gradient_boosting:max_bins,regressor:gradient_boosting:max_depth,regressor:gradient_boosting:max_leaf_nodes,regressor:gradient_boosting:min_samples_leaf,regressor:gradient_boosting:n_iter_no_change,regressor:gradient_boosting:scoring,regressor:gradient_boosting:tol,regressor:gradient_boosting:validation_fraction,regressor:k_nearest_neighbors:n_neighbors,regressor:k_nearest_neighbors:p,regressor:k_nearest_neighbors:weights,regressor:liblinear_svr:C,regressor:liblinear_svr:dual,regressor:liblinear_svr:epsilon,regressor:liblinear_svr:fit_intercept,regressor:liblinear_svr:intercept_scaling,regressor:liblinear_svr:loss,regressor:liblinear_svr:tol,regressor:libsvm_svr:C,regressor:libsvm_svr:coef0,regressor:libsvm_svr:degree,regressor:libsvm_svr:epsilon,regressor:libsvm_svr:gamma,regressor:libsvm_svr:kernel,regressor:libsvm_svr:max_iter,regressor:libsvm_svr:shrinking,regressor:libsvm_svr:tol,regressor:mlp:activation,regressor:mlp:alpha,regressor:mlp:batch_size,regressor:mlp:beta_1,regressor:mlp:beta_2,regressor:mlp:early_stopping,regressor:mlp:epsilon,regressor:mlp:hidden_layer_depth,regressor:mlp:learning_rate_init,regressor:mlp:n_iter_no_change,regressor:mlp:num_nodes_per_layer,regressor:mlp:shuffle,regressor:mlp:solver,regressor:mlp:tol,regressor:mlp:validation_fraction,regressor:random_forest:bootstrap,regressor:random_forest:criterion,regressor:random_forest:max_depth,regressor:random_forest:max_features,regressor:random_forest:max_leaf_nodes,regressor:random_forest:min_impurity_decrease,regressor:random_forest:min_samples_leaf,regressor:random_forest:min_samples_split,regressor:random_forest:min_weight_fraction_leaf,regressor:sgd:alpha,regressor:sgd:average,regressor:sgd:epsilon,regressor:sgd:eta0,regressor:sgd:fit_intercept,regressor:sgd:l1_ratio,regressor:sgd:learning_rate,regressor:sgd:loss,regressor:sgd:penalty,regressor:sgd:power_t,regressor:sgd:tol,data_preprocessor:__choice__,data_preprocessor:feature_type:text_transformer:feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:__choice__,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:use_idf,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:ngram_upper_bound
 2,no_encoding,no_coalescense,,most_frequent,standardize,,,,,select_rates_regression,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.1,fpr,f_regression,gaussian_process,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.019645201003537352,1.1170068633409441e-07,130.632960269528,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,feature_type,100,bag_of_word_encoding,1,min_df_absolute,,,,,,,,,1
 6,one_hot_encoding,minority_coalescer,0.000400759453878678,mean,minmax,,,,,select_rates_regression,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.09988990258830989,fpr,f_regression,gradient_boosting,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,off,3.0002886744200357e-06,0.015673535665067875,least_squares,255,None,7,23,,loss,1e-07,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,feature_type,100,bag_of_word_encoding,1,min_df_absolute,,,,,,,,,1
 7,one_hot_encoding,no_coalescense,,most_frequent,quantile_transformer,809,uniform,,,polynomial,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,3,False,True,,,,,,,,,,,,,sgd,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.01806079811541296,False,,0.015540128437738566,True,0.9326390049807726,constant,squared_loss,elasticnet,,0.00010576654619459039,feature_type,100,bag_of_word_encoding,1,min_df_absolute,,,,,,,,,1
diff --git a/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding.py b/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding.py
index 47a80684f7..b8a62ccd89 100644
--- a/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding.py
+++ b/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding.py
@@ -17,13 +17,13 @@
 class BagOfWordEncoder(AutoSklearnPreprocessingAlgorithm):
     def __init__(
         self,
-        ngram_range: int = 1,
+        ngram_upper_bound: int = 1,
         min_df_choice: str = "min_df_absolute",
         min_df_absolute: int = 0,
         min_df_relative: float = 0.01,
         random_state: Optional[Union[int, np.random.RandomState]] = None,
     ) -> None:
-        self.ngram_range = ngram_range
+        self.ngram_upper_bound = ngram_upper_bound
         self.random_state = random_state
         self.min_df_choice = min_df_choice
         self.min_df_absolute = min_df_absolute
@@ -46,13 +46,13 @@ def fit(
         if self.min_df_choice == "min_df_absolute":
             self.preprocessor = CountVectorizer(
                 min_df=self.min_df_absolute,
-                ngram_range=(1, self.ngram_range),
+                ngram_range=(1, self.ngram_upper_bound),
             )
 
         elif self.min_df_choice == "min_df_relative":
             self.preprocessor = CountVectorizer(
                 min_df=self.min_df_relative,
-                ngram_range=(1, self.ngram_range),
+                ngram_range=(1, self.ngram_upper_bound),
             )
 
         else:
@@ -98,8 +98,8 @@ def get_hyperparameter_search_space(
         dataset_properties: Optional[DATASET_PROPERTIES_TYPE] = None,
     ) -> ConfigurationSpace:
         cs = ConfigurationSpace()
-        hp_ngram_range = CSH.UniformIntegerHyperparameter(
-            name="ngram_range", lower=1, upper=3, default_value=1
+        hp_ngram_upper_bound = CSH.UniformIntegerHyperparameter(
+            name="ngram_upper_bound", lower=1, upper=3, default_value=1
         )
         hp_min_df_choice_bow = CSH.CategoricalHyperparameter(
             "min_df_choice", choices=["min_df_absolute", "min_df_relative"]
@@ -112,7 +112,7 @@ def get_hyperparameter_search_space(
         )
         cs.add_hyperparameters(
             [
-                hp_ngram_range,
+                hp_ngram_upper_bound,
                 hp_min_df_choice_bow,
                 hp_min_df_absolute_bow,
                 hp_min_df_relative_bow,
diff --git a/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding_distinct.py b/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding_distinct.py
index 22a0be1088..90a43b0f48 100644
--- a/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding_distinct.py
+++ b/autosklearn/pipeline/components/data_preprocessing/text_encoding/bag_of_word_encoding_distinct.py
@@ -16,13 +16,13 @@
 class BagOfWordEncoder(AutoSklearnPreprocessingAlgorithm):
     def __init__(
         self,
-        ngram_range: int = 1,
+        ngram_upper_bound: int = 1,
         min_df_choice: str = "min_df_absolute",
         min_df_absolute: int = 0,
         min_df_relative: float = 0.01,
         random_state: Optional[Union[int, np.random.RandomState]] = None,
     ) -> None:
-        self.ngram_range = ngram_range
+        self.ngram_upper_bound = ngram_upper_bound
         self.random_state = random_state
         self.min_df_choice = min_df_choice
         self.min_df_absolute = min_df_absolute
@@ -40,7 +40,8 @@ def fit(
 
                 for feature in X.columns:
                     vectorizer = CountVectorizer(
-                        min_df=self.min_df_absolute, ngram_range=(1, self.ngram_range)
+                        min_df=self.min_df_absolute,
+                        ngram_range=(1, self.ngram_upper_bound),
                     ).fit(X[feature])
                     self.preprocessor[feature] = vectorizer
 
@@ -50,7 +51,8 @@ def fit(
 
                 for feature in X.columns:
                     vectorizer = CountVectorizer(
-                        min_df=self.min_df_relative, ngram_range=(1, self.ngram_range)
+                        min_df=self.min_df_relative,
+                        ngram_range=(1, self.ngram_upper_bound),
                     ).fit(X[feature])
                     self.preprocessor[feature] = vectorizer
             else:
@@ -102,8 +104,8 @@ def get_hyperparameter_search_space(
         dataset_properties: Optional[DATASET_PROPERTIES_TYPE] = None,
     ) -> ConfigurationSpace:
         cs = ConfigurationSpace()
-        hp_ngram_range = CSH.UniformIntegerHyperparameter(
-            name="ngram_range", lower=1, upper=3, default_value=1
+        hp_ngram_upper_bound = CSH.UniformIntegerHyperparameter(
+            name="ngram_upper_bound", lower=1, upper=3, default_value=1
         )
         hp_min_df_choice_bow = CSH.CategoricalHyperparameter(
             "min_df_choice", choices=["min_df_absolute", "min_df_relative"]
@@ -116,7 +118,7 @@ def get_hyperparameter_search_space(
         )
         cs.add_hyperparameters(
             [
-                hp_ngram_range,
+                hp_ngram_upper_bound,
                 hp_min_df_choice_bow,
                 hp_min_df_absolute_bow,
                 hp_min_df_relative_bow,
diff --git a/autosklearn/pipeline/components/data_preprocessing/text_encoding/tfidf_encoding.py b/autosklearn/pipeline/components/data_preprocessing/text_encoding/tfidf_encoding.py
index aea4a05906..f20d24f769 100644
--- a/autosklearn/pipeline/components/data_preprocessing/text_encoding/tfidf_encoding.py
+++ b/autosklearn/pipeline/components/data_preprocessing/text_encoding/tfidf_encoding.py
@@ -17,14 +17,14 @@
 class TfidfEncoder(AutoSklearnPreprocessingAlgorithm):
     def __init__(
         self,
-        ngram_range: int = 1,
+        ngram_upper_bound: int = 1,
         use_idf: bool = True,
         min_df_choice: str = "min_df_absolute",
         min_df_absolute: int = 0,
         min_df_relative: float = 0.01,
         random_state: Optional[Union[int, np.random.RandomState]] = None,
     ) -> None:
-        self.ngram_range = ngram_range
+        self.ngram_upper_bound = ngram_upper_bound
         self.random_state = random_state
         self.use_idf = use_idf
         self.min_df_choice = min_df_choice
@@ -50,14 +50,14 @@ def fit(
             self.preprocessor = TfidfVectorizer(
                 min_df=self.min_df_absolute,
                 use_idf=self.use_idf,
-                ngram_range=(1, self.ngram_range),
+                ngram_range=(1, self.ngram_upper_bound),
             )
 
         elif self.min_df_choice == "min_df_relative":
             self.preprocessor = TfidfVectorizer(
                 min_df=self.min_df_relative,
                 use_idf=self.use_idf,
-                ngram_range=(1, self.ngram_range),
+                ngram_range=(1, self.ngram_upper_bound),
             )
 
         else:
@@ -103,8 +103,8 @@ def get_hyperparameter_search_space(
         dataset_properties: Optional[DATASET_PROPERTIES_TYPE] = None,
     ) -> ConfigurationSpace:
         cs = ConfigurationSpace()
-        hp_ngram_range = CSH.UniformIntegerHyperparameter(
-            name="ngram_range", lower=1, upper=3, default_value=1
+        hp_ngram_upper_bound = CSH.UniformIntegerHyperparameter(
+            name="ngram_upper_bound", lower=1, upper=3, default_value=1
         )
         hp_use_idf = CSH.CategoricalHyperparameter("use_idf", choices=[False, True])
         hp_min_df_choice = CSH.CategoricalHyperparameter(
@@ -118,7 +118,7 @@ def get_hyperparameter_search_space(
         )
         cs.add_hyperparameters(
             [
-                hp_ngram_range,
+                hp_ngram_upper_bound,
                 hp_use_idf,
                 hp_min_df_choice,
                 hp_min_df_absolute,
diff --git a/examples/40_advanced/example_text_preprocessing.py b/examples/40_advanced/example_text_preprocessing.py
index 76c2d91cfc..7c65825b7b 100644
--- a/examples/40_advanced/example_text_preprocessing.py
+++ b/examples/40_advanced/example_text_preprocessing.py
@@ -1,79 +1,84 @@
 # -*- encoding: utf-8 -*-
 """
 ==================
-Text Preprocessing
+Text preprocessing
 ==================
-This example shows, how to use text features in *auto-sklearn*. *auto-sklearn* can automatically
-encode text features if they are provided as string type in a pandas dataframe.
 
-For processing text features you need a pandas dataframe and set the desired
-text columns to string and the categorical columns to category.
+The following example shows how to fit a simple NLP problem with
+*auto-sklearn*.
 
-*auto-sklearn* text embedding creates a bag of words count.
+For an introduction to text preprocessing you can follow these links:
+    1. https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
+    2. https://machinelearningmastery.com/clean-text-machine-learning-python/
 """
+from pprint import pprint
+
+import pandas as pd
 import sklearn.metrics
-import sklearn.datasets
+from sklearn.datasets import fetch_20newsgroups
+
 import autosklearn.classification
 
 ############################################################################
 # Data Loading
 # ============
+cats = ["comp.sys.ibm.pc.hardware", "rec.sport.baseball"]
+X_train, y_train = fetch_20newsgroups(
+    subset="train",  # select train set
+    shuffle=True,  # shuffle the data set for unbiased validation results
+    random_state=42,  # set a random seed for reproducibility
+    categories=cats,  # select only 2 out of 20 labels
+    return_X_y=True,  # 20NG dataset consists of 2 columns X: the text data, y: the label
+)  # load this two columns separately as numpy array
+
+X_test, y_test = fetch_20newsgroups(
+    subset="test",  # select test set for unbiased evaluation
+    categories=cats,  # select only 2 out of 20 labels
+    return_X_y=True,  # 20NG dataset consists of 2 columns X: the text data, y: the label
+)  # load this two columns separately as numpy array
 
-X, y = sklearn.datasets.fetch_openml(data_id=40945, return_X_y=True)
-
-# by default, the columns which should be strings are not formatted as such
-print(f"{X.info()}\n")
-
-# manually convert these to string columns
-X = X.astype(
-    {
-        "name": "string",
-        "ticket": "string",
-        "cabin": "string",
-        "boat": "string",
-        "home.dest": "string",
-    }
-)
+############################################################################
+# Creating a pandas dataframe
+# ===========================
+# Both categorical and text features are often strings. Python Pandas stores python stings
+# in the generic `object` type. Please ensure that the correct
+# `dtype <https://pandas.pydata.org/docs/user_guide/basics.html#dtypes>`_ is applied to the correct
+# column.
 
-# now *auto-sklearn* handles the string columns with its text feature preprocessing pipeline
+# create a pandas dataframe for training labeling the "Text" column as sting
+X_train = pd.DataFrame({"Text": pd.Series(X_train, dtype="string")})
 
-X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(
-    X, y, random_state=1
-)
+# create a pandas dataframe for testing labeling the "Text" column as sting
+X_test = pd.DataFrame({"Text": pd.Series(X_test, dtype="string")})
 
-cls = autosklearn.classification.AutoSklearnClassifier(
-    time_left_for_this_task=30,
-    # Bellow two flags are provided to speed up calculations
-    # Not recommended for a real implementation
-    initial_configurations_via_metalearning=0,
-    smac_scenario_args={"runcount_limit": 1},
+############################################################################
+# Build and fit a classifier
+# ==========================
+
+# create an autosklearn Classifier or Regressor depending on your task at hand.
+automl = autosklearn.classification.AutoSklearnClassifier(
+    time_left_for_this_task=60,
+    per_run_time_limit=30,
+    tmp_folder="/tmp/autosklearn_text_example_tmp",
 )
 
-cls.fit(X_train, y_train, X_test, y_test)
-
-predictions = cls.predict(X_test)
-print("Accuracy score", sklearn.metrics.accuracy_score(y_test, predictions))
+automl.fit(X_train, y_train, dataset_name="20_Newsgroups")  # fit the automl model
 
+############################################################################
+# View the models found by auto-sklearn
+# =====================================
 
-X, y = sklearn.datasets.fetch_openml(data_id=40945, return_X_y=True, as_frame=True)
-X = X.select_dtypes(exclude=["object"])
+print(automl.leaderboard())
 
-X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(
-    X, y, random_state=1
-)
+############################################################################
+# Print the final ensemble constructed by auto-sklearn
+# ====================================================
 
-cls = autosklearn.classification.AutoSklearnClassifier(
-    time_left_for_this_task=30,
-    # Bellow two flags are provided to speed up calculations
-    # Not recommended for a real implementation
-    initial_configurations_via_metalearning=0,
-    smac_scenario_args={"runcount_limit": 1},
-)
+pprint(automl.show_models(), indent=4)
 
-cls.fit(X_train, y_train, X_test, y_test)
+###########################################################################
+# Get the Score of the final ensemble
+# ===================================
 
-predictions = cls.predict(X_test)
-print(
-    "Accuracy score without text preprocessing",
-    sklearn.metrics.accuracy_score(y_test, predictions),
-)
+predictions = automl.predict(X_test)
+print("Accuracy score:", sklearn.metrics.accuracy_score(y_test, predictions))
diff --git a/test/test_metalearning/pyMetaLearn/test_meta_base_data/configurations.csv b/test/test_metalearning/pyMetaLearn/test_meta_base_data/configurations.csv
index 0336e76f01..e36bd31d4a 100755
--- a/test/test_metalearning/pyMetaLearn/test_meta_base_data/configurations.csv
+++ b/test/test_metalearning/pyMetaLearn/test_meta_base_data/configurations.csv
@@ -1,4 +1,4 @@
-idx,balancing:strategy,classifier:__choice__,classifier:adaboost:algorithm,classifier:adaboost:learning_rate,classifier:adaboost:max_depth,classifier:adaboost:n_estimators,classifier:bernoulli_nb:alpha,classifier:bernoulli_nb:fit_prior,classifier:decision_tree:criterion,classifier:decision_tree:max_depth_factor,classifier:decision_tree:max_features,classifier:decision_tree:max_leaf_nodes,classifier:decision_tree:min_impurity_decrease,classifier:decision_tree:min_samples_leaf,classifier:decision_tree:min_samples_split,classifier:decision_tree:min_weight_fraction_leaf,classifier:extra_trees:bootstrap,classifier:extra_trees:criterion,classifier:extra_trees:max_depth,classifier:extra_trees:max_features,classifier:extra_trees:max_leaf_nodes,classifier:extra_trees:min_impurity_decrease,classifier:extra_trees:min_samples_leaf,classifier:extra_trees:min_samples_split,classifier:extra_trees:min_weight_fraction_leaf,classifier:gradient_boosting:early_stop,classifier:gradient_boosting:l2_regularization,classifier:gradient_boosting:learning_rate,classifier:gradient_boosting:loss,classifier:gradient_boosting:max_bins,classifier:gradient_boosting:max_depth,classifier:gradient_boosting:max_leaf_nodes,classifier:gradient_boosting:min_samples_leaf,classifier:gradient_boosting:n_iter_no_change,classifier:gradient_boosting:scoring,classifier:gradient_boosting:tol,classifier:gradient_boosting:validation_fraction,classifier:k_nearest_neighbors:n_neighbors,classifier:k_nearest_neighbors:p,classifier:k_nearest_neighbors:weights,classifier:lda:shrinkage,classifier:lda:shrinkage_factor,classifier:lda:tol,classifier:liblinear_svc:C,classifier:liblinear_svc:dual,classifier:liblinear_svc:fit_intercept,classifier:liblinear_svc:intercept_scaling,classifier:liblinear_svc:loss,classifier:liblinear_svc:multi_class,classifier:liblinear_svc:penalty,classifier:liblinear_svc:tol,classifier:libsvm_svc:C,classifier:libsvm_svc:coef0,classifier:libsvm_svc:degree,classifier:libsvm_svc:gamma,classifier:libsvm_svc:kernel,classifier:libsvm_svc:max_iter,classifier:libsvm_svc:shrinking,classifier:libsvm_svc:tol,classifier:multinomial_nb:alpha,classifier:multinomial_nb:fit_prior,classifier:passive_aggressive:C,classifier:passive_aggressive:average,classifier:passive_aggressive:fit_intercept,classifier:passive_aggressive:loss,classifier:passive_aggressive:tol,classifier:qda:reg_param,classifier:random_forest:bootstrap,classifier:random_forest:criterion,classifier:random_forest:max_depth,classifier:random_forest:max_features,classifier:random_forest:max_leaf_nodes,classifier:random_forest:min_impurity_decrease,classifier:random_forest:min_samples_leaf,classifier:random_forest:min_samples_split,classifier:random_forest:min_weight_fraction_leaf,classifier:sgd:alpha,classifier:sgd:average,classifier:sgd:epsilon,classifier:sgd:eta0,classifier:sgd:fit_intercept,classifier:sgd:l1_ratio,classifier:sgd:learning_rate,classifier:sgd:loss,classifier:sgd:penalty,classifier:sgd:power_t,classifier:sgd:tol,data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction,data_preprocessor:feature_type:numerical_transformer:imputation:strategy,data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:n_quantiles,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:output_distribution,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_max,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_min,feature_preprocessor:__choice__,feature_preprocessor:extra_trees_preproc_for_classification:bootstrap,feature_preprocessor:extra_trees_preproc_for_classification:criterion,feature_preprocessor:extra_trees_preproc_for_classification:max_depth,feature_preprocessor:extra_trees_preproc_for_classification:max_features,feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes,feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease,feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf,feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split,feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf,feature_preprocessor:extra_trees_preproc_for_classification:n_estimators,feature_preprocessor:fast_ica:algorithm,feature_preprocessor:fast_ica:fun,feature_preprocessor:fast_ica:n_components,feature_preprocessor:fast_ica:whiten,feature_preprocessor:feature_agglomeration:affinity,feature_preprocessor:feature_agglomeration:linkage,feature_preprocessor:feature_agglomeration:n_clusters,feature_preprocessor:feature_agglomeration:pooling_func,feature_preprocessor:kernel_pca:coef0,feature_preprocessor:kernel_pca:degree,feature_preprocessor:kernel_pca:gamma,feature_preprocessor:kernel_pca:kernel,feature_preprocessor:kernel_pca:n_components,feature_preprocessor:kitchen_sinks:gamma,feature_preprocessor:kitchen_sinks:n_components,feature_preprocessor:liblinear_svc_preprocessor:C,feature_preprocessor:liblinear_svc_preprocessor:dual,feature_preprocessor:liblinear_svc_preprocessor:fit_intercept,feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling,feature_preprocessor:liblinear_svc_preprocessor:loss,feature_preprocessor:liblinear_svc_preprocessor:multi_class,feature_preprocessor:liblinear_svc_preprocessor:penalty,feature_preprocessor:liblinear_svc_preprocessor:tol,feature_preprocessor:nystroem_sampler:coef0,feature_preprocessor:nystroem_sampler:degree,feature_preprocessor:nystroem_sampler:gamma,feature_preprocessor:nystroem_sampler:kernel,feature_preprocessor:nystroem_sampler:n_components,feature_preprocessor:pca:keep_variance,feature_preprocessor:pca:whiten,feature_preprocessor:polynomial:degree,feature_preprocessor:polynomial:include_bias,feature_preprocessor:polynomial:interaction_only,feature_preprocessor:random_trees_embedding:bootstrap,feature_preprocessor:random_trees_embedding:max_depth,feature_preprocessor:random_trees_embedding:max_leaf_nodes,feature_preprocessor:random_trees_embedding:min_samples_leaf,feature_preprocessor:random_trees_embedding:min_samples_split,feature_preprocessor:random_trees_embedding:min_weight_fraction_leaf,feature_preprocessor:random_trees_embedding:n_estimators,feature_preprocessor:select_percentile_classification:percentile,feature_preprocessor:select_percentile_classification:score_func,feature_preprocessor:select_rates_classification:alpha,feature_preprocessor:select_rates_classification:mode,feature_preprocessor:select_rates_classification:score_func,data_preprocessor:__choice__,data_preprocessor:feature_type:text_transformer:feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:__choice__,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:use_idf,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:ngram_range
+idx,balancing:strategy,classifier:__choice__,classifier:adaboost:algorithm,classifier:adaboost:learning_rate,classifier:adaboost:max_depth,classifier:adaboost:n_estimators,classifier:bernoulli_nb:alpha,classifier:bernoulli_nb:fit_prior,classifier:decision_tree:criterion,classifier:decision_tree:max_depth_factor,classifier:decision_tree:max_features,classifier:decision_tree:max_leaf_nodes,classifier:decision_tree:min_impurity_decrease,classifier:decision_tree:min_samples_leaf,classifier:decision_tree:min_samples_split,classifier:decision_tree:min_weight_fraction_leaf,classifier:extra_trees:bootstrap,classifier:extra_trees:criterion,classifier:extra_trees:max_depth,classifier:extra_trees:max_features,classifier:extra_trees:max_leaf_nodes,classifier:extra_trees:min_impurity_decrease,classifier:extra_trees:min_samples_leaf,classifier:extra_trees:min_samples_split,classifier:extra_trees:min_weight_fraction_leaf,classifier:gradient_boosting:early_stop,classifier:gradient_boosting:l2_regularization,classifier:gradient_boosting:learning_rate,classifier:gradient_boosting:loss,classifier:gradient_boosting:max_bins,classifier:gradient_boosting:max_depth,classifier:gradient_boosting:max_leaf_nodes,classifier:gradient_boosting:min_samples_leaf,classifier:gradient_boosting:n_iter_no_change,classifier:gradient_boosting:scoring,classifier:gradient_boosting:tol,classifier:gradient_boosting:validation_fraction,classifier:k_nearest_neighbors:n_neighbors,classifier:k_nearest_neighbors:p,classifier:k_nearest_neighbors:weights,classifier:lda:shrinkage,classifier:lda:shrinkage_factor,classifier:lda:tol,classifier:liblinear_svc:C,classifier:liblinear_svc:dual,classifier:liblinear_svc:fit_intercept,classifier:liblinear_svc:intercept_scaling,classifier:liblinear_svc:loss,classifier:liblinear_svc:multi_class,classifier:liblinear_svc:penalty,classifier:liblinear_svc:tol,classifier:libsvm_svc:C,classifier:libsvm_svc:coef0,classifier:libsvm_svc:degree,classifier:libsvm_svc:gamma,classifier:libsvm_svc:kernel,classifier:libsvm_svc:max_iter,classifier:libsvm_svc:shrinking,classifier:libsvm_svc:tol,classifier:multinomial_nb:alpha,classifier:multinomial_nb:fit_prior,classifier:passive_aggressive:C,classifier:passive_aggressive:average,classifier:passive_aggressive:fit_intercept,classifier:passive_aggressive:loss,classifier:passive_aggressive:tol,classifier:qda:reg_param,classifier:random_forest:bootstrap,classifier:random_forest:criterion,classifier:random_forest:max_depth,classifier:random_forest:max_features,classifier:random_forest:max_leaf_nodes,classifier:random_forest:min_impurity_decrease,classifier:random_forest:min_samples_leaf,classifier:random_forest:min_samples_split,classifier:random_forest:min_weight_fraction_leaf,classifier:sgd:alpha,classifier:sgd:average,classifier:sgd:epsilon,classifier:sgd:eta0,classifier:sgd:fit_intercept,classifier:sgd:l1_ratio,classifier:sgd:learning_rate,classifier:sgd:loss,classifier:sgd:penalty,classifier:sgd:power_t,classifier:sgd:tol,data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__,data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction,data_preprocessor:feature_type:numerical_transformer:imputation:strategy,data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:n_quantiles,data_preprocessor:feature_type:numerical_transformer:rescaling:quantile_transformer:output_distribution,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_max,data_preprocessor:feature_type:numerical_transformer:rescaling:robust_scaler:q_min,feature_preprocessor:__choice__,feature_preprocessor:extra_trees_preproc_for_classification:bootstrap,feature_preprocessor:extra_trees_preproc_for_classification:criterion,feature_preprocessor:extra_trees_preproc_for_classification:max_depth,feature_preprocessor:extra_trees_preproc_for_classification:max_features,feature_preprocessor:extra_trees_preproc_for_classification:max_leaf_nodes,feature_preprocessor:extra_trees_preproc_for_classification:min_impurity_decrease,feature_preprocessor:extra_trees_preproc_for_classification:min_samples_leaf,feature_preprocessor:extra_trees_preproc_for_classification:min_samples_split,feature_preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf,feature_preprocessor:extra_trees_preproc_for_classification:n_estimators,feature_preprocessor:fast_ica:algorithm,feature_preprocessor:fast_ica:fun,feature_preprocessor:fast_ica:n_components,feature_preprocessor:fast_ica:whiten,feature_preprocessor:feature_agglomeration:affinity,feature_preprocessor:feature_agglomeration:linkage,feature_preprocessor:feature_agglomeration:n_clusters,feature_preprocessor:feature_agglomeration:pooling_func,feature_preprocessor:kernel_pca:coef0,feature_preprocessor:kernel_pca:degree,feature_preprocessor:kernel_pca:gamma,feature_preprocessor:kernel_pca:kernel,feature_preprocessor:kernel_pca:n_components,feature_preprocessor:kitchen_sinks:gamma,feature_preprocessor:kitchen_sinks:n_components,feature_preprocessor:liblinear_svc_preprocessor:C,feature_preprocessor:liblinear_svc_preprocessor:dual,feature_preprocessor:liblinear_svc_preprocessor:fit_intercept,feature_preprocessor:liblinear_svc_preprocessor:intercept_scaling,feature_preprocessor:liblinear_svc_preprocessor:loss,feature_preprocessor:liblinear_svc_preprocessor:multi_class,feature_preprocessor:liblinear_svc_preprocessor:penalty,feature_preprocessor:liblinear_svc_preprocessor:tol,feature_preprocessor:nystroem_sampler:coef0,feature_preprocessor:nystroem_sampler:degree,feature_preprocessor:nystroem_sampler:gamma,feature_preprocessor:nystroem_sampler:kernel,feature_preprocessor:nystroem_sampler:n_components,feature_preprocessor:pca:keep_variance,feature_preprocessor:pca:whiten,feature_preprocessor:polynomial:degree,feature_preprocessor:polynomial:include_bias,feature_preprocessor:polynomial:interaction_only,feature_preprocessor:random_trees_embedding:bootstrap,feature_preprocessor:random_trees_embedding:max_depth,feature_preprocessor:random_trees_embedding:max_leaf_nodes,feature_preprocessor:random_trees_embedding:min_samples_leaf,feature_preprocessor:random_trees_embedding:min_samples_split,feature_preprocessor:random_trees_embedding:min_weight_fraction_leaf,feature_preprocessor:random_trees_embedding:n_estimators,feature_preprocessor:select_percentile_classification:percentile,feature_preprocessor:select_percentile_classification:score_func,feature_preprocessor:select_rates_classification:alpha,feature_preprocessor:select_rates_classification:mode,feature_preprocessor:select_rates_classification:score_func,data_preprocessor:__choice__,data_preprocessor:feature_type:text_transformer:feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:__choice__,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_feature_reduction:n_components,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding_distinct:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_absolute,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_choice,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:min_df_relative,data_preprocessor:feature_type:text_transformer:text_encoding:tfidf_encoding:use_idf,data_preprocessor:feature_type:text_transformer:text_encoding:bag_of_word_encoding:ngram_upper_bound
 1,none,gradient_boosting,,,,,,,,,,,,,,,,,,,,,,,,off,0.006832691101653281,0.0990420448281782,auto,255,None,58,9,,loss,1E-07,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,one_hot_encoding,minority_coalescer,0.047607909209835673,most_frequent,normalize,,,,,feature_agglomeration,,,,,,,,,,,,,,,cosine,average,72,median,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,feature_type,100,bag_of_word_encoding,1,,min_df_absolute,,,,,,,,,1
 2,none,gradient_boosting,,,,,,,,,,,,,,,,,,,,,,,,off,2.215660250704945e-08,0.0568967527929491,auto,255,None,74,58,,loss,1E-07,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,one_hot_encoding,no_coalescense,,most_frequent,none,,,,,select_rates_classification,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.3999502319254789,fwe,f_classif,feature_type,100,bag_of_word_encoding,1,,min_df_absolute,,,,,,,,,1
 3,none,random_forest,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,True,entropy,None,0.7811236762098946,None,0.0,15,9,0.0,,,,,,,,,,,,no_encoding,no_coalescense,,most_frequent,none,,,,,extra_trees_preproc_for_classification,False,entropy,None,0.2269858618750471,None,0.0,13,12,0.0,100,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,feature_type,100,bag_of_word_encoding,1,,min_df_absolute,,,,,,,,,1
diff --git a/test/test_pipeline/components/data_preprocessing/test_data_preprocessing_text.py b/test/test_pipeline/components/data_preprocessing/test_data_preprocessing_text.py
index 0a2e3d5188..c0729b1dfc 100644
--- a/test/test_pipeline/components/data_preprocessing/test_data_preprocessing_text.py
+++ b/test/test_pipeline/components/data_preprocessing/test_data_preprocessing_text.py
@@ -20,7 +20,7 @@ def test_fit_transform(self):
             }
         ).astype({"col1": "string", "col2": "string"})
         BOW_fitted = BOW(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -46,7 +46,7 @@ def test_fit_transform(self):
         np.testing.assert_array_equal(Yt, Y)
 
         BOW_fitted = BOW_distinct(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -69,7 +69,7 @@ def test_transform(self):
             }
         ).astype({"col1": "string", "col2": "string"})
         X_t = BOW(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -81,7 +81,7 @@ def test_transform(self):
         np.testing.assert_array_equal(X_t.toarray(), y)
 
         X_t = BOW_distinct(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -103,7 +103,7 @@ def test_check_shape(self):
             }
         ).astype({"col1": "string", "col2": "string"})
         X_t = BOW(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -113,7 +113,7 @@ def test_check_shape(self):
         self.assertEqual(X_t.shape, (2, 5))
 
         X_t = BOW_distinct(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -130,7 +130,7 @@ def test_check_nan(self):
             }
         ).astype({"col1": "string", "col2": "string"})
         X_t = BOW(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,
@@ -140,7 +140,7 @@ def test_check_nan(self):
         self.assertEqual(X_t.shape, (3, 5))
 
         X_t = BOW_distinct(
-            ngram_range=1,
+            ngram_upper_bound=1,
             min_df_choice="min_df_absolute",
             min_df_absolute=0,
             min_df_relative=0,