def tnr(y_true, y_pred, round=True):
    """True negative rate `tn / (tn + fp)`
    """
    y_true, y_pred = _mask_value_nan(y_true, y_pred)
    if round:
        y_true = np.round(y_true)
        y_pred = np.round(y_pred)
    c = skm.confusion_matrix(y_true, y_pred)
    return c[0, 0] / c[0].sum()
def tnr ( y_true , y_pred , round = True ) : y_true , y_pred = _mask_value_nan ( y_true , y_pred ) if round : y_true = np . round ( y_true ) y_pred = np . round ( y_pred ) c = skm . confusion_matrix ( y_true , y_pred ) return c [ 0 , 0 ] / c [ 0 ] . sum ( )
True negative rate `tn / (tn + fp)`