evalml.model_understanding.graph_roc_curve

evalml.model_understanding.graph_roc_curve(y_true, y_pred_proba, custom_class_names=None, title_addition=None)[source]

Generate and display a Receiver Operating Characteristic (ROC) plot for binary and multiclass classification problems.

Parameters

  • y_true (ww.DataColumn, pd.Series or np.ndarray) – True labels.

  • y_pred_proba (ww.DataColumn, pd.Series or np.ndarray) – Predictions from a classifier, before thresholding has been applied. Note this should a one dimensional array with the predicted probability for the “true” label in the binary case.

  • custom_class_labels (list or None) – If not None, custom labels for classes. Default None.

  • title_addition (str or None) – if not None, append to plot title. Default None.

Returns

plotly.Figure representing the ROC plot generated

evalml.model_understanding.graph_precision_recall_curve evalml.model_understanding.graph_confusion_matrix