From c0e9b157daa5116de806a1d47186faceff48f462 Mon Sep 17 00:00:00 2001
From: Jesse Leigh Patsolic <StudioJLP@gmail.com>
Date: Wed, 2 Oct 2019 13:35:16 -0400
Subject: [PATCH] fix string -> int

---
 ...classification_using_structured_RerF.ipynb | 23 ++++++++++---------
 1 file changed, 12 insertions(+), 11 deletions(-)

diff --git a/docs/demos/S-RerF/MNIST_classification_using_structured_RerF.ipynb b/docs/demos/S-RerF/MNIST_classification_using_structured_RerF.ipynb
index 2cd8066f..74462b77 100644
--- a/docs/demos/S-RerF/MNIST_classification_using_structured_RerF.ipynb
+++ b/docs/demos/S-RerF/MNIST_classification_using_structured_RerF.ipynb
@@ -40,7 +40,8 @@
     "train_samples = 5000\n",
     "\n",
     "# Load data from https://www.openml.org/d/554\n",
-    "X, y = fetch_openml('mnist_784', version=1, return_X_y=True)"
+    "X, y = fetch_openml('mnist_784', version=1, return_X_y=True)\n",
+    "y = y.astype(int)"
    ]
   },
   {
@@ -73,12 +74,12 @@
      "output_type": "stream",
      "text": [
       "rerfClassifier(feature_combinations=1.5, image_height=None, image_width=None,\n",
-      "               max_depth=None, max_features='auto', min_parent=1,\n",
+      "               max_depth=None, max_features='auto', min_samples_split=1,\n",
       "               n_estimators=100, n_jobs=8, oob_score=False,\n",
       "               patch_height_max=None, patch_height_min=1, patch_width_max=None,\n",
       "               patch_width_min=1, projection_matrix='Base', random_state=None)\n",
       "rerfClassifier(feature_combinations=1.5, image_height=28, image_width=28,\n",
-      "               max_depth=None, max_features='auto', min_parent=1,\n",
+      "               max_depth=None, max_features='auto', min_samples_split=1,\n",
       "               n_estimators=100, n_jobs=8, oob_score=False, patch_height_max=5,\n",
       "               patch_height_min=1, patch_width_max=5, patch_width_min=1,\n",
       "               projection_matrix='S-RerF', random_state=None)\n"
@@ -110,7 +111,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "run time rerf 0.7958900928497314\n"
+      "run time rerf 1.1266508102416992\n"
      ]
     }
    ],
@@ -130,7 +131,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "run time s_rerf 3.6138932704925537\n"
+      "run time s_rerf 6.353916883468628\n"
      ]
     }
    ],
@@ -158,10 +159,10 @@
     }
    ],
    "source": [
-    "train_acc_rerf = clf_rerf.score(X_train, y_train.astype(int))\n",
+    "train_acc_rerf = clf_rerf.score(X_train, y_train)\n",
     "print(\"train_acc rerf\", train_acc_rerf)\n",
     "\n",
-    "train_acc_s_rerf = clf_s_rerf.score(X_train, y_train.astype(int))\n",
+    "train_acc_s_rerf = clf_s_rerf.score(X_train, y_train)\n",
     "print(\"train_acc s_rerf\", train_acc_s_rerf)"
    ]
   },
@@ -176,18 +177,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "score rerf 0.9361\n",
-      "score s_rerf 0.9427\n"
+      "score rerf 0.9376\n",
+      "score s_rerf 0.9436\n"
      ]
     }
    ],
    "source": [
     "# sparsity = np.mean(clf.coef_ == 0) * 100\n",
-    "score = clf_rerf.score(X_test, y_test.astype(int))\n",
+    "score = clf_rerf.score(X_test, y_test)\n",
     "print(\"score rerf\", score)\n",
     "\n",
     "# sparsity = np.mean(clf.coef_ == 0) * 100\n",
-    "score = clf_s_rerf.score(X_test, y_test.astype(int))\n",
+    "score = clf_s_rerf.score(X_test, y_test)\n",
     "print(\"score s_rerf\", score)"
    ]
   }