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
| 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) |
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)