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Review comments: spacing and results doc
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@dhimmel
dhimmel committed Sep 26, 2016
1 parent 527963b commit e926c5d
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10 changes: 8 additions & 2 deletions cognoml/analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,12 @@ def classify(sample_id, mutation_status, **kwargs):
Sample IDs of the observations.
mutation_status : list
Mutation status (0 or 1) of each sample.
Returns
-------
results : dict
A JSON-serializable object. OrderedDicts are used for dictionaries to
enable reproducibile export.
"""
results = collections.OrderedDict()

Expand Down Expand Up @@ -80,8 +86,8 @@ def classify(sample_id, mutation_status, **kwargs):

performance = collections.OrderedDict()
for part, df in ('training', obs_train_df), ('testing', obs_test_df):
y_true=df.status
y_pred=df.predicted_status
y_true = df.status
y_pred = df.predicted_status
metrics = utils.class_metrics(y_true, y_pred)
metrics.update(utils.threshold_metrics(y_true, y_pred))
performance[part] = utils.value_map(metrics, round, ndigits=5)
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345 changes: 345 additions & 0 deletions hippo-output-schema.json
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Original file line number Diff line number Diff line change
@@ -0,0 +1,345 @@
{
"required": [
"dimensions",
"grid_search",
"model",
"observations",
"performance"
],
"type": "object",
"properties": {
"performance": {
"required": [
"cv",
"testing",
"training"
],
"type": "object",
"properties": {
"cv": {
"required": [
"auroc"
],
"type": "object",
"properties": {
"auroc": {
"type": "number"
}
}
},
"training": {
"required": [
"accuracy",
"auprc",
"auroc",
"balanced_accuracy",
"f1",
"precision",
"recall"
],
"type": "object",
"properties": {
"accuracy": {
"type": "number"
},
"recall": {
"type": "number"
},
"auroc": {
"type": "number"
},
"balanced_accuracy": {
"type": "number"
},
"precision": {
"type": "number"
},
"auprc": {
"type": "number"
},
"f1": {
"type": "number"
}
}
},
"testing": {
"required": [
"accuracy",
"auprc",
"auroc",
"balanced_accuracy",
"f1",
"precision",
"recall"
],
"type": "object",
"properties": {
"accuracy": {
"type": "number"
},
"recall": {
"type": "number"
},
"auroc": {
"type": "number"
},
"balanced_accuracy": {
"type": "number"
},
"precision": {
"type": "number"
},
"auprc": {
"type": "number"
},
"f1": {
"type": "number"
}
}
}
}
},
"grid_search": {
"required": [
"fold_scores",
"mean_scores"
],
"type": "object",
"properties": {
"mean_scores": {
"required": [
"columns",
"data"
],
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"type": "array",
"items": {
"type": "number"
}
}
},
"columns": {
"type": "array",
"items": {
"type": "string"
}
}
}
},
"fold_scores": {
"required": [
"columns",
"data"
],
"type": "object",
"properties": {
"data": {
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"items": {
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"items": {
"type": "number"
}
}
},
"columns": {
"type": "array",
"items": {
"type": "string"
}
}
}
}
}
},
"model": {
"required": [
"class",
"features",
"module",
"parameters"
],
"type": "object",
"properties": {
"class": {
"type": "string"
},
"parameters": {
"required": [
"alpha",
"average",
"class_weight",
"epsilon",
"eta0",
"fit_intercept",
"l1_ratio",
"learning_rate",
"loss",
"n_iter",
"n_jobs",
"penalty",
"power_t",
"random_state",
"shuffle",
"verbose",
"warm_start"
],
"type": "object",
"properties": {
"penalty": {
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},
"shuffle": {
"type": "boolean"
},
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},
"fit_intercept": {
"type": "boolean"
},
"eta0": {
"type": "number"
},
"epsilon": {
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},
"average": {
"type": "boolean"
},
"random_state": {
"type": "integer"
},
"alpha": {
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},
"power_t": {
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},
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"type": "integer"
},
"verbose": {
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},
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"type": "number"
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},
"learning_rate": {
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},
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"type": "boolean"
},
"class_weight": {
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}
}
},
"features": {
"required": [
"columns",
"data"
],
"type": "object",
"properties": {
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"type": "array",
"items": {
"type": "array",
"items": {
"type": [
"number",
"string"
]
}
}
},
"columns": {
"type": "array",
"items": {
"type": "string"
}
}
}
},
"module": {
"type": "string"
}
}
},
"observations": {
"required": [
"columns",
"data"
],
"type": "object",
"properties": {
"data": {
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"items": {
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"number",
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]
}
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"items": {
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}
}
}
},
"dimensions": {
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"negatives",
"observations_selected",
"observations_unselected",
"positive_prevalence",
"positives",
"testing_observations",
"training_observations"
],
"type": "object",
"properties": {
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"type": "integer"
},
"training_observations": {
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},
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"type": "integer"
},
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"type": "number"
},
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"features": {
"type": "integer"
},
"observations_unselected": {
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},
"observations_selected": {
"type": "integer"
}
}
}
}
}

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