Function forward

ann_logistic_extra/ann_train.py:40–42

(X, W1, b1, W2, b2)

    return expA / expA.sum(axis=1, keepdims=True)

def forward(X, W1, b1, W2, b2):
    Z = np.tanh(X.dot(W1) + b1)
    return softmax(Z.dot(W2) + b2), Z

def predict(P_Y_given_X):
    return np.argmax(P_Y_given_X, axis=1)