Function cost_function

machine_learning/logistic_regression.py:31–32

(h, y)

def cost_function(h, y):
    return (-y * np.log(h) - (1 - y) * np.log(1 - h)).mean()


# here alpha is the learning rate, X is the feature matrix,y is the target matrix