如何基于AUC指标在Keras中保存最佳模型? [英] How to save best model in Keras based on AUC metric?

问题描述

我想基于auc在Keras中保存最佳模型，并且我有以下代码:

I would like to save the best model in Keras based on auc and I have this code:

def MyMetric(yTrue, yPred):
    auc = tf.metrics.auc(yTrue, yPred)
    return auc

best_model = [ModelCheckpoint(filepath='best_model.h5', monitor='MyMetric', save_best_only=True)]

train_history = model.fit([train_x], 
          [train_y], batch_size=batch_size, epochs=epochs, validation_split=0.05, 
                          callbacks=best_model, verbose = 2)

因此我的模型运行不正常，我收到此警告:

SO my model runs nut I get this warning:

RuntimeWarning: Can save best model only with MyMetric available, skipping.
  'skipping.' % (self.monitor), RuntimeWarning)

如果能告诉我这是正确的方法，那是很好的，否则我该怎么办?

It would be great if any can tell me this is the right way to do it and if not what should I do?

推荐答案

您必须将要监视的指标传递给model.compile.

You have to pass the Metric you want to monitor to model.compile.

https://keras.io/metrics/#custom-metrics

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=[MyMetric])

此外，tf.metrics.auc返回一个包含张量和update_op的元组. Keras希望自定义指标功能仅返回张量.

Also, tf.metrics.auc returns a tuple containing the tensor and update_op. Keras expects the custom metric function to return only a tensor.

def MyMetric(yTrue, yPred):
    import tensorflow as tf
    auc = tf.metrics.auc(yTrue, yPred)
    return auc[0]

在此步骤之后，您将获得有关未初始化值的错误.请查看以下主题:

After this step, you will get errors about uninitialized values. Please see these threads:

https://github.com/keras-team/keras/issues/3230

如何计算接收运行特征( ROC)和keras中的AUC?

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