Python import_libsvm_sparseの例

コード例 #1

ファイル: test_realdata.py プロジェクト: yuqianxiangguan/libact

 def setUp(self):
     dataset_filepath = os.path.join(
         os.path.dirname(os.path.realpath(__file__)),
         'datasets/heart_scale')
     self.X, self.y = import_libsvm_sparse(
         dataset_filepath).format_sklearn()
     self.quota = 10

コード例 #2

ファイル: nn_active_learning.py プロジェクト: PAL-UH/active_learning

def split_train_test(dataset_filepath, test_size, n_labeled):
    X, y = import_libsvm_sparse(dataset_filepath).format_sklearn()

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=42, shuffle=True)
    trn_ds = Dataset(X_train, np.concatenate([y_train[:n_labeled], [None] * (len(y_train) - n_labeled)]))
    tst_ds = Dataset(X_test, y_test)
    fully_labeled_trn_ds = Dataset(X_train, y_train)

    return trn_ds, tst_ds, y_train, fully_labeled_trn_ds

コード例 #3

ファイル: plot.py プロジェクト: ntucllab/libact

def split_train_test(dataset_filepath, test_size, n_labeled):
    X, y = import_libsvm_sparse(dataset_filepath).format_sklearn()

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size)
    trn_ds = Dataset(X_train, np.concatenate([y_train[:n_labeled], [None] * (len(y_train) - n_labeled)]))
    tst_ds = Dataset(X_test, y_test)
    fully_labeled_trn_ds = Dataset(X_train, y_train)

    return trn_ds, tst_ds, y_train, fully_labeled_trn_ds

コード例 #4

ファイル: plot.py プロジェクト: yenchih/libact

def split_train_test():
    dataset_filepath = os.path.join(
        os.path.dirname(os.path.realpath(__file__)), 'diabetes.txt')
    X, y = import_libsvm_sparse(dataset_filepath).format_sklearn()

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)

    n_labeled = 10

    trn_ds = Dataset(X_train, np.concatenate([y_train[:n_labeled], [None] * (len(y_train) - n_labeled)]))
    tst_ds = Dataset(X_test, y_test)
    fully_labeled_trn_ds = Dataset(X_train, y_train)

    return trn_ds, tst_ds, y_train, fully_labeled_trn_ds

コード例 #5

ファイル: albl_plot.py プロジェクト: yiyg510/libact

def split_train_test(dataset_filepath, test_size, n_labeled):
    X, y = import_libsvm_sparse(dataset_filepath).format_sklearn()

    X_train, X_test, y_train, y_test = \
        train_test_split(X, y, test_size=test_size)

    while len(np.unique((y_train[:n_labeled]))) != 2:
        X_train, X_test, y_train, y_test = \
            train_test_split(X, y, test_size=test_size)

    trn_ds = Dataset(X_train, np.concatenate(
        [y_train[:n_labeled], [None] * (len(y_train) - n_labeled)]))
    tst_ds = Dataset(X_test, y_test)
    fully_labeled_trn_ds = Dataset(X_train, y_train)

    return trn_ds, tst_ds, y_train, fully_labeled_trn_ds

コード例 #6

ファイル: test_realdata.py プロジェクト: Edgar324/libact

 def setUp(self):
     dataset_filepath = os.path.join(
         os.path.dirname(os.path.realpath(__file__)), 'datasets/heart_scale')
     self.X, self.y = import_libsvm_sparse(
         dataset_filepath).format_sklearn()
     self.quota = 10