    # 'sklearn.preprocessing.Binarizer': {
    #     'threshold': np.arange(0.0, 1.01, 0.05)
    # },

    # 'sklearn.decomposition.FastICA': {
    #     'tol': np.arange(0.0, 1.01, 0.05)
    # },

    # 'sklearn.cluster.FeatureAgglomeration': {
    #     'linkage': ['ward', 'complete', 'average'],
    #     'affinity': ['euclidean', 'l1', 'l2', 'manhattan', 'cosine']
    # },

    # 'sklearn.preprocessing.MaxAbsScaler': {
    # },

    # 'sklearn.preprocessing.MinMaxScaler': {
    # },

    # 'sklearn.preprocessing.Normalizer': {
    #     'norm': ['l1', 'l2', 'max']
    # },

    # 'sklearn.kernel_approximation.Nystroem': {
    #     'kernel': ['rbf', 'cosine', 'chi2', 'laplacian', 'polynomial', 'poly', 'linear', 'additive_chi2', 'sigmoid'],
    #     'gamma': np.arange(0.0, 1.01, 0.05),
    #     'n_components': range(1, 11)
    # },

    # 'sklearn.decomposition.PCA': {
    #     'svd_solver': ['randomized'],
    #     'iterated_power': range(1, 11)
    # },

    # 'sklearn.preprocessing.PolynomialFeatures': {
    #     'degree': [2],
    #     'include_bias': [False],
    #     'interaction_only': [False]
    # },


    # FactorAnalysis, LatentDirichletAllocation