Warning
DEPRECATED
-
sklearn.grid_search.fit_grid_point(X, y, estimator, parameters, train, test, scorer, verbose, error_score='raise', **fit_params)[source] -
Run fit on one set of parameters.
Deprecated since version 0.18: This module will be removed in 0.20. Use
sklearn.model_selection.fit_grid_pointinstead.Parameters: X : array-like, sparse matrix or list
Input data.
y : array-like or None
Targets for input data.
estimator : estimator object
A object of that type is instantiated for each grid point. This is assumed to implement the scikit-learn estimator interface. Either estimator needs to provide a
scorefunction, orscoringmust be passed.parameters : dict
Parameters to be set on estimator for this grid point.
train : ndarray, dtype int or bool
Boolean mask or indices for training set.
test : ndarray, dtype int or bool
Boolean mask or indices for test set.
scorer : callable or None.
If provided must be a scorer callable object / function with signature
scorer(estimator, X, y).verbose : int
Verbosity level.
**fit_params : kwargs
Additional parameter passed to the fit function of the estimator.
error_score : ?raise? (default) or numeric
Value to assign to the score if an error occurs in estimator fitting. If set to ?raise?, the error is raised. If a numeric value is given, FitFailedWarning is raised. This parameter does not affect the refit step, which will always raise the error.
Returns: score : float
Score of this parameter setting on given training / test split.
parameters : dict
The parameters that have been evaluated.
n_samples_test : int
Number of test samples in this split.
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