Function derivative_W

ann_class/regression.py:70–73

(X, Z, Y, Yhat, V)

  return (Y - Yhat).sum()

def derivative_W(X, Z, Y, Yhat, V):
  # dZ = np.outer(Y - Yhat, V) * (1 - Z * Z) # this is for tanh activation
  dZ = np.outer(Y - Yhat, V) * (Z > 0) # relu
  return X.T.dot(dZ)

def derivative_b(Z, Y, Yhat, V):
  # dZ = np.outer(Y - Yhat, V) * (1 - Z * Z) # this is for tanh activation