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: Predict on given X.
docstr_tok: ["Predict","on","given","X","."]
code: def predict(self, X):  # pylint: disable=invalid-name
      """Predict on given X."""
      return np.random.uniform(
          self.min_value, self.max_value, X.shape[0]
      )
  
imports: import numpy
label_desc: Use image node_id 3 for calling the RegressionUniformModel obj's underlying member method code with example usage: obj.predict(X) and returns: np