tf_util.py 文件源码

def explained_variance_1d(ypred,y):
    """
    Var[ypred - y] / var[y]. 
    https://www.quora.com/What-is-the-meaning-proportion-of-variance-explained-in-linear-regression
    """
    assert y.ndim == 1 and ypred.ndim == 1    
    vary = np.var(y)
    return np.nan if vary==0 else 1 - np.var(y-ypred)/vary