class_docstr: K-means
  
  Performs k-means clustering on an H2O dataset.
class_docstr_tok: ["K-means","Performs","k-means","clustering","on","an","H2O","dataset","."]
code: def categorical_encoding(self, categorical_encoding):
      assert_is_type(
          categorical_encoding,
          None,
          Enum(
              "auto",
              "enum",
              "one_hot_internal",
              "one_hot_explicit",
              "binary",
              "eigen",
              "label_encoder",
              "sort_by_response",
              "enum_limited",
          ),
      )
      self._parms["categorical_encoding"] = categorical_encoding
  
imports: from h2o.estimators.estimator_base import H2OEstimator
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.utils.typechecks import assert_is_type, Enum, numeric
label_desc: Use image node_id 41 for calling the H2OKMeansEstimator obj's underlying member method code with example usage: obj.categorical_encoding(categorical_encoding) without return types