stpredictions.models.OK3.tests package

Submodules

stpredictions.models.OK3.tests.digits_image_completion module

stpredictions.models.OK3.tests.exemple_utilisation module

stpredictions.models.OK3.tests.exemple_utilisation_forest module

stpredictions.models.OK3.tests.test_classification module

stpredictions.models.OK3.tests.test_classification.test_classification_multilabel(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_classification.test_classification_multilabel_ref(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_classification_forest module

stpredictions.models.OK3.tests.test_classification_forest.test_classification_multilabel(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_classification_forest.test_classification_multilabel_ref(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_export module

stpredictions.models.OK3.tests.test_forest_clf_and_reg module

Testing for the forest module (sklearn.ensemble.forest).

class stpredictions.models.OK3.tests.test_forest_clf_and_reg.MyBackend(*args, **kwargs)

Bases: joblib._parallel_backends.LokyBackend

start_call()

Call-back method called at the beginning of a Parallel call

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_1d_input(name, kernel, X, X_2d, y)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_classification_toy(name)

Check classification on a toy dataset.

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_decision_path(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_gridsearch(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_importances(name, criterion, kernel, dtype, tolerance)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_iris_criterion(name, criterion)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_max_leaf_nodes_max_depth(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_memory_layout(name, kernel, dtype)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_min_impurity_decrease(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_min_impurity_split(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_min_samples_leaf(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_min_samples_split(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_min_weight_fraction_leaf(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_multioutput(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_oob_score(name, X, y, kernel, n_estimators=20)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_oob_score_raise_error(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_parallel(name, kernel, X, y)

Check parallel computations in classification

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_pickle(name, kernel, X, y)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_regression_criterion(name, criterion)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_sparse_input(name, kernel, X, X_sparse, y)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_warm_start(name, kernel, random_state=42)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_warm_start_clear(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_warm_start_equal_n_estimators(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_warm_start_oob(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.check_warm_start_smaller_n_estimators(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_1d_input(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_backend_respected()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_classification_toy(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_decision_path(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_distribution()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_dtype_convert(n_classes=15)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_forest_degenerate_feature_importances()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_forest_feature_importances_sum()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_forest_y_sparse()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_gridsearch(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_importances(dtype, name, criterion, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_iris(name, criterion)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_little_tree_with_small_max_samples(kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_max_leaf_nodes_max_depth(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_max_samples_exceptions(name, kernel, max_samples, exc_type, exc_msg)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_memory_layout(name, kernel, dtype)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_min_impurity_decrease(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_min_impurity_split(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_min_samples_leaf(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_min_samples_split(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_min_weight_fraction_leaf(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_multioutput(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_multioutput_string(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_oob_score_classifiers(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_oob_score_raise_error(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_oob_score_regressors(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_parallel(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_parallel_train()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_pickle(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_random_hasher()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_random_hasher_sparse_data()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_random_trees_dense_equal()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_random_trees_dense_type()

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_regression(name, criterion)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_sparse_input(name, kernel, sparse_matrix)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_unfitted_feature_importances(name)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_warm_start(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_warm_start_clear(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_warm_start_equal_n_estimators(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_warm_start_oob(name, kernel)

stpredictions.models.OK3.tests.test_forest_clf_and_reg.test_warm_start_smaller_n_estimators(name, kernel)

stpredictions.models.OK3.tests.test_regression module

stpredictions.models.OK3.tests.test_regression.test_regression(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_regression.test_regression_ref(X_train, y_train, X_test, y_test)

Return the mse for a classical regression task

stpredictions.models.OK3.tests.test_regression_forest module

stpredictions.models.OK3.tests.test_regression_forest.test_regression(X_train, y_train, X_test, y_test)

Return the test accuracy for a multiclass classification task

stpredictions.models.OK3.tests.test_regression_forest.test_regression_ref(X_train, y_train, X_test, y_test)

Return the mse for a classical regression task

stpredictions.models.OK3.tests.test_tree_clf_and_reg module

Testing for the tree module (sklearn.tree).

stpredictions.models.OK3.tests.test_tree_clf_and_reg.assert_is_subtree(tree, subtree)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.assert_pruning_creates_subtree(estimator_cls, X, y, pruning_path, kernel)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.assert_tree_equal(d, s, message)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_apply_path_readonly(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_decision_path(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_explicit_sparse_zeros(tree, max_depth=3, n_features=10)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_min_weight_fraction_leaf(name, datasets, sparse=False)

Test if leaves contain at least min_weight_fraction_leaf of the training set

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_min_weight_fraction_leaf_with_min_samples_leaf(name, datasets, sparse=False)

Test the interaction between min_weight_fraction_leaf and min_samples_leaf when sample_weights is not provided in fit.

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_min_weight_leaf_split_level(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_no_sparse_y_support(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_public_apply(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_public_apply_sparse(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_raise_error_on_1d_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_sparse_criterion(tree, dataset)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_sparse_input(tree, dataset, max_depth=None, only_reg=False)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.check_sparse_parameters(tree, dataset)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_1d_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_X_idx_sorted_deprecated(TreeEstimator)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_apply_path_readonly_all_trees(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_arrayrepr()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_arrays_persist()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_behaviour_constant_feature_after_splits()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_big_input()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_classification_toy()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_criterion_copy()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_decision_path(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_decision_path_hardcoded()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_diabetes_overfit(name, Tree, criterion)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_diabetes_underfit(name, Tree, criterion, max_depth)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_empty_leaf_infinite_threshold()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_error()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_explicit_sparse_zeros(tree_type)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_huge_allocations()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_importances()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_importances_gini_equal_mse()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_importances_raises()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_iris()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_max_features()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_max_leaf_nodes()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_max_leaf_nodes_max_depth()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_memory_layout()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_impurity_decrease()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_impurity_split()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_samples_leaf()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_samples_split()

Test min_samples_split parameter

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_weight_fraction_leaf_on_dense_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_weight_fraction_leaf_on_sparse_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_weight_fraction_leaf_with_min_samples_leaf_on_dense_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_weight_fraction_leaf_with_min_samples_leaf_on_sparse_input(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_min_weight_leaf_split_level(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_multioutput()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_no_sparse_y_support(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_numerical_stability()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_only_constant_features()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_prune_single_node_tree()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_prune_tree_classifier_are_subtrees(criterion, dataset, tree_cls)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_prune_tree_raises_negative_ccp_alpha()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_prune_tree_regression_are_subtrees(criterion, dataset, tree_cls)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_public_apply_all_trees(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_public_apply_sparse_trees(name)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_pure_set()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_realloc()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_regression_toy()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_sample_weight()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_sample_weight_invalid()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_sparse(tree_type, dataset, check)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_sparse_input(tree_type, dataset)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_sparse_input_reg_trees(tree_type, dataset)

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_unbalanced_iris()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_weighted_classification_toy()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_with_only_one_non_constant_features()

stpredictions.models.OK3.tests.test_tree_clf_and_reg.test_xor()

Module contents