{
  "sklearn": {
    "modules": {
      "cluster": {
        "functions": [{ "name": "KMeans", "returns": "KMeans" }],
        "types": {
          "KMeans": {
            "methods": [
              { "name": "fit", "updates": [0] },
              { "name": "fit_predict", "updates": [0] },
              { "name": "fit_transform", "updates": [0] },
              "predict",
              "score",
              "transform"
            ]
          }
        }
      },

      "datasets": {
        "functions": [
          "clear_data_home",
          "dump_svmlight_file",
          "fetch_20newsgroups",
          "fetch_20newsgroups_vectorized",
          "fetch_lfw_pairs",
          "fetch_lfw_people",
          "fetch_mldata",
          "fetch_olivetti_faces",
          "fetch_species_distributions",
          "fetch_california_housing",
          "fetch_covtype",
          "fetch_rcv1",
          "fetch_kddcup99",
          "fetch_openml",
          "get_data_home",
          "load_boston",
          "load_diabetes",
          "load_digits",
          "load_files",
          "load_iris",
          "load_breast_cancer",
          "load_linnerud",
          "load_mlcomp",
          "load_sample_image",
          "load_sample_images",
          "load_svmlight_file",
          "load_svmlight_files",
          "load_wine",
          "make_biclusters",
          "make_blobs",
          "make_circles",
          "make_classification",
          "make_checkerboard",
          "make_friedman1",
          "make_friedman2",
          "make_friedman3",
          "make_gaussian_quantiles",
          "make_hastie_10_2",
          "make_low_rank_matrix",
          "make_moons",
          "make_multilabel_classification",
          "make_regression",
          "make_s_curve",
          "make_sparse_coded_signal",
          "make_sparse_spd_matrix",
          "make_sparse_uncorrelated",
          "make_spd_matrix",
          "make_swiss_roll",
          "mldata_filename"
        ]
      }
    }
  }
}