probinet.model_selection.main

Main module for running cross-validation for different algorithms.

Functions

cross_validation(algorithm, ...[, ...])

Run cross-validation for a given algorithm.

probinet.model_selection.main.cross_validation(algorithm: str, model_parameters: dict[str, Any], cv_parameters: dict[str, Any], numerical_parameters: dict[str, Any] | None = None) → DataFrame

Run cross-validation for a given algorithm. :param algorithm: String with the name of the algorithm to run. :param model_parameters: Dictionary with the parameters for the algorithm. :param cv_parameters: Dictionary with the parameters for the cross-validation. :param numerical_parameters: Dictionary with the numerical parameters for the algorithm, like the number of iterations, etc.

Returns:

DataFrame with the results of the cross-validation.

Return type:

results_df