evalml.model_understanding.binary_objective_vs_threshold

evalml.model_understanding.binary_objective_vs_threshold(pipeline, X, y, objective, steps=100)[source]
Computes objective score as a function of potential binary classification

decision thresholds for a fitted binary classification pipeline.

Parameters

  • pipeline (BinaryClassificationPipeline obj) – Fitted binary classification pipeline

  • X (ww.DataTable, pd.DataFrame) – The input data used to compute objective score

  • y (ww.DataColumn, pd.Series) – The target labels

  • objective (ObjectiveBase obj, str) – Objective used to score

  • steps (int) – Number of intervals to divide and calculate objective score at

Returns

DataFrame with thresholds and the corresponding objective score calculated at each threshold

Return type

pd.DataFrame

evalml.model_understanding.calculate_permutation_importance evalml.model_understanding.get_prediction_vs_actual_over_time_data