ML.INSPECT.DECISION_BOUNDARY¶
Extracts the decision boundary contour points for a classifier and input data X.
Syntax¶
ML.INSPECT.DECISION_BOUNDARY(model, X, response_method, mesh_step, class_pair, feature_indices, other_features_values, margin)
Arguments¶
| Name | Type | Default | Description |
|---|---|---|---|
| model | object | Fitted classifier with predict or decision_function method | |
| X | object | numpy array or pandas DataFrame of predictors (n_samples, n_features) | |
| response_method | str | "predict" | predict or decision_function |
| mesh_step | float | 0.05 | step size for the mesh grid |
| class_pair | list[int] | [0, 1] | tuple of two ints (for multiclass decision_function), e.g., (0, 1) or (1, 0) |
| feature_indices | tuple[int, int] | (0, 1) | tuple of two ints indicating which features to use for boundary calculation |
| other_features_values | dict[int, float] | None | dict or None. If dict, keys are feature indices and values are the values to use for other features |
| margin | float | 0.1 | Positional argument 8 |
Examples¶
Examples coming soon
Working Excel formula examples for this function are not yet written.