maplezzz / ntu_ml2017_hung-yi-lee_hw Goto Github PK

def GD(X, Y, w, eta, iteration, lambdaL2):
    list_cost = []
    for i in range(iteration):
        hypo = np.dot(X, w)
        loss = hypo - Y
        cost = np.sum(loss ** 2) / len(X)
        list_cost.append(cost)
       # 求grad的时候，不需要*2吗
        grad = np.dot(X.T, loss) / len(X) + lambdaL2 * w
        w = w - eta * grad
    return w, list_cost