

def test_random_hasher_sparse_data():
    (X, y) = datasets.make_multilabel_classification(random_state=0)
    hasher = RandomTreesEmbedding(n_estimators=30, random_state=1)
    X_transformed = hasher.fit_transform(X_transformed)
    X_transformed_sparse = hasher.fit_transform(csc_matrix(X))
    assert_array_equal(X_transformed_sparse.toarray(), X_transformed.toarray())

dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/tests/test_forest.py test_random_hasher_sparse_data/VarMisuse@43/67 `X`->`X_transformed`