evalml.model_understanding.
precision_recall_curve
Given labels and binary classifier predicted probabilities, compute and return the data representing a precision-recall curve.
y_true (ww.DataColumn, pd.Series or np.ndarray) – True binary labels.
y_pred_proba (ww.DataColumn, pd.Series or np.ndarray) – Predictions from a binary classifier, before thresholding has been applied. Note this should be the predicted probability for the “true” label.
Dictionary containing metrics used to generate a precision-recall plot, with the following keys:
precision: Precision values. recall: Recall values. thresholds: Threshold values used to produce the precision and recall. auc_score: The area under the ROC curve.
precision: Precision values.
recall: Recall values.
thresholds: Threshold values used to produce the precision and recall.
auc_score: The area under the ROC curve.
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