class_docstr: Model used to randomly predict from given series of labels.
class_docstr_tok: ["Model","used","to","randomly","predict","from","given","series","of","labels","."]
docstr: Fit model.
docstr_tok: ["Fit","model","."]
code: def fit(self, X, y):  # pylint: disable=unused-argument,invalid-name
      """Fit model."""
      # The X is not used, but it is needed to be matching to sklearn `fit` signature
      self.labels = y
  
imports: import numpy
label_desc: Use image node_id 2 for calling the RandomModel obj's underlying member method code with example usage: obj.fit(X, y) without return types