nmf.py 文件源码

def divergence(self, V, W, H):
        """
        Compute divergence between reconstruction and original
        """    

        R = np.maximum(np.dot(W,H), eps)
        V = np.maximum(V, eps)
        err = 0
        if self.update == self.kl_updates:
            err = np.sum(np.multiply(V, np.log(V/R)) - V + R)
        elif self.update == self.euc_updates:
            err = np.sum((V - np.dot(W,H)) ** 2)
        elif self.update == self.is_updates:
            err = np.sum(V/R - np.log(V/R) - 1)
        elif self.update == self.beta_updates:
            err = (np.sum(V ** self.beta + (self.beta -1) * R ** self.beta
                  - self.beta * V * R ** (self.beta - 1)) 
                  / (self.beta * (self.beta - 1)))
        return err