class_docstr: Model that draws predictions uniformly at random from the range of values in y.
class_docstr_tok: ["Model","that","draws","predictions","uniformly","at","random","from","the","range","of","values","in","y","."]
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.min_value = y.min()
      self.max_value = y.max()
  
imports: import numpy
label_desc: Use image node_id 2 for calling the RegressionUniformModel obj's underlying member method code with example usage: obj.fit(X, y) without return types