unbeatableregressor.py

# define a sklearn compatible wrapper for our data generating function
class UnbeatableRegressor():
    
    def __init__(self):
        pass
    
    def fit(self, X, y):
        pass  
    
    def predict(self, X):
        return np.array(X2y(X, with_error = False))
    
    def score(self, X, y):
        return mean_absolute_error(y, self.predict(X))