iota2.learning.train_sklearn

Functions

can_perform_cv(cv_paramerters, clf)	check if the cross validation can be done
cast_config_cv_parameters(config_cv_parameters)	cast cross validation parameters coming from config to a compatible sklearn type
force_proba(sk_classifier)	force the classifier model to be able of generate proabilities
get_learning_samples(learning_samples_dir, ...)	get sorted learning samples files from samples directory
model_name_to_function(model_name)	cast the model'name from string to sklearn object
save_cross_val_best_param(output_path, clf)	save cross validation parameters in a text file
sk_learn(dataset_path, features_labels, ...)	Train a model thanks to scikit-learn