hw4.py 文件源码

def generate_quadratic_parameters(trials):
    """ax^2 + b"""
    def transform(x):
        """
        transform             
        x1  --->   1 x1**2
        """
        ones = np.ones(len(x))
        x1 = x[:, 0]
        x1_sqr = x1 ** 2 
        return np.stack([ones, x1_sqr], axis=1)

    new_trials = [
            DataML((training_set.z, training_set.y), transform)
        for training_set in trials ]
    weights = [ linear_percepton(training_set.z, training_set.y) for training_set in new_trials ]
    return np.array(weights)