Tensorflow计算正确率、精确率、召回率

Tensorflow计算正确率、精确率、召回率

二分类模型的评价指标

https://www.cnblogs.com/xiaoniu-666/p/10511694.html

参考tf的方法

    predictions = tf.argmax(predict, 1)

    actuals = tf.argmax(real, 1)

    ones_like_actuals = tf.ones_like(actuals)

    zeros_like_actuals = tf.zeros_like(actuals)

    ones_like_predictions = tf.ones_like(predictions)

    zeros_like_predictions = tf.zeros_like(predictions)

        Lable:      1   1   0   0

        predi:      1   0   0   1

                    Tp  Fp  Tn  Fn

    tp: = and       1

    tn = ont(or)            1

    lab-pred:       0   1   0   -1

    lab-pred>=0.6:  0   1   0   0

    fp = and(lable, lab-pred):

                    0   1   0   1

    lab-pred<=-1.0: 0   0   0   1

    not-lable:      0   0   1   1

    fn = and(not-lable, lab-pred<-1.0)

可能用到的方法：

tf.less_equal

tf.less

tf.greater_equal

tf.greater
count_nonzero

参考：

https://blog.csdn.net/sinat_35821976/article/details/81334181

https://tensorflow.google.cn/api_docs/python/tf/math/count_nonzero