Пример #1
0
    def go_by_category(category):
        input = TrainingFactory.build_sparse_matrix_target(limit=10000)
        targets = TrainingFactory.build_target_vector_by_category(category,limit=10000)

        input_train, input_test, target_train, target_test = train_test_split(input, targets, test_size=0.1)

        classif = SVC(kernel='rbf', tol=0.001, probability=True)
        classif.fit(input_train, target_train)

        output_targets = classif.predict(input_test)
        print output_targets
        print target_test
        print
Пример #2
0
    def go_by_category(category):
        input = TrainingFactory.build_sparse_matrix_target(limit=10000)
        targets = TrainingFactory.build_target_vector_by_category(category,
                                                                  limit=10000)

        input_train, input_test, target_train, target_test = train_test_split(
            input, targets, test_size=0.1)

        classif = SVC(kernel='rbf', tol=0.001, probability=True)
        classif.fit(input_train, target_train)

        output_targets = classif.predict(input_test)
        print output_targets
        print target_test
        print
Пример #3
0
    def go():

        input = TrainingFactory.build_sparse_matrix_input(limit=10000)
        targets = TrainingFactory.build_sparse_matrix_target(limit=10000)

        input_train, input_test, target_train, target_test = train_test_split(input, targets, test_size=0.1)

        classif = OneVsRestClassifier(SVC(kernel='rbf', tol=0.001, probability=True))
        classif.fit(input_train, target_train)

        output_targets = classif.predict_proba(input_test)
        print ClassifierFactory.output_function(output_targets)
        print ClassifierFactory.output_function(target_test.todense())

        print log_loss(target_test, output_targets)
        print
Пример #4
0
    def go():

        input = TrainingFactory.build_sparse_matrix_input(limit=10000)
        targets = TrainingFactory.build_sparse_matrix_target(limit=10000)

        input_train, input_test, target_train, target_test = train_test_split(
            input, targets, test_size=0.1)

        classif = OneVsRestClassifier(
            SVC(kernel='rbf', tol=0.001, probability=True))
        classif.fit(input_train, target_train)

        output_targets = classif.predict_proba(input_test)
        print ClassifierFactory.output_function(output_targets)
        print ClassifierFactory.output_function(target_test.todense())

        print log_loss(target_test, output_targets)
        print