inspection.importance.plot_feature_scatter_matrix

inspection.importance.plot_feature_scatter_matrix(
    X,
    y,
    feature_names,
    target_names,
    top_features,
    target_index,
    figsize=(6, 6),
)

Generate scatter plot matrix for the most important features.

Parameters

Name Type Description Default
X np.ndarray Input features array required
y np.ndarray Target array required
feature_names list List of feature names required
target_names list List of target names required
top_features list List of top feature names to include required
target_index int Index of target variable to analyze required
figsize tuple Size of the figure (6, 6)

Returns

Name Type Description
None None

Examples

>>> from spotoptim.sensitivity import plot_feature_scatter_matrix
>>> import pandas as pd
>>> from sklearn.datasets import make_regression
>>> X, y = make_regression(n_samples=100, n_features=5, noise=0.1, random_state=42)
>>> feature_names = [f"feature_{i}" for i in range(X.shape[1])]
>>> target_names = ["target"]
>>> top_features = ["feature_0", "feature_1", "feature_2"]
>>> plot_feature_scatter_matrix(X, y, feature_names, target_names, top_features, target_index=0)