force_plots¶
Module Contents¶
Functions¶
Function to generate the data required to build a force plot. |
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Function to generate force plots for the desired rows of the training data. |
Contents¶
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evalml.model_understanding.force_plots.force_plot(pipeline, rows_to_explain, training_data, y)[source]¶ Function to generate the data required to build a force plot.
- Parameters
pipeline (PipelineBase) – The pipeline to generate the force plot for.
rows_to_explain (list(int)) – A list of the indices of the training_data to explain.
training_data (pandas.DataFrame) – The data used to train the pipeline.
y (pandas.Series) – The target data.
- Returns
- list of dictionaries where each dict contains force plot data. Each dictionary
entry represents the explanations for a single row.
- For single row binary force plots:
- [{‘malignant’: {‘expected_value’: 0.37,
’feature_names’: [‘worst concave points’, ‘worst perimeter’, ‘worst radius’], ‘shap_values’: [0.09, 0.09, 0.08], ‘plot’: AdditiveForceVisualizer}]
- For two row binary force plots:
- [{‘malignant’: {‘expected_value’: 0.37,
’feature_names’: [‘worst concave points’, ‘worst perimeter’, ‘worst radius’], ‘shap_values’: [0.09, 0.09, 0.08], ‘plot’: AdditiveForceVisualizer},
- {‘malignant’: {‘expected_value’: 0.29,
’feature_names’: [‘worst concave points’, ‘worst perimeter’, ‘worst radius’], ‘shap_values’: [0.05, 0.03, 0.02], ‘plot’: AdditiveForceVisualizer}]
- Return type
list(dict())
- Raises
TypeError – if rows_to_explain is not a list.
TypeError – if all values in rows_to_explain aren’t integers.
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evalml.model_understanding.force_plots.graph_force_plot(pipeline, rows_to_explain, training_data, y, matplotlib=False)[source]¶ Function to generate force plots for the desired rows of the training data.
- Parameters
pipeline (PipelineBase) – The pipeline to generate the force plot for.
rows_to_explain (list(int)) – A list of the indices indicating which of the rows of the training_data to explain.
training_data (pandas.DataFrame) – The data used to train the pipeline.
y (pandas.Series) – The target data for the pipeline.
matplotlib (bool) – flag to display the force plot using matplotlib (outside of jupyter) Defaults to False.
- Returns
- The same as force_plot(), but with an additional
key in each dictionary for the plot.
- Return type
list(dict(shap.AdditiveForceVisualizer))