python - 训练期间每类验证的准确性

Question

Keras 在训练期间给出了整体训练和验证的准确性。

有什么方法可以在训练期间获得每类验证准确性？

更新来自 Pycharm 的错误日志

File "C:/Users/wj96hq/PycharmProjects/PedestrianClassification/Awareness.py", line 82, in <module>
shuffle=True, callbacks=callbacks)
File "C:\Users\wj96hq\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py", line 66, in _method_wrapper
return method(self, *args, **kwargs)
File "C:\Users\wj96hq\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py", line 876, in fit
callbacks.on_epoch_end(epoch, epoch_logs)
File "C:\Users\wj96hq\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\callbacks.py", line 365, in on_epoch_end
callback.on_epoch_end(epoch, logs)
File "C:/Users/wj96hq/PycharmProjects/PedestrianClassification/Awareness.py", line 36, in on_epoch_end
x_test, y_test = self.validation_data[0], self.validation_data[1]
TypeError: 'NoneType' object is not subscriptable

Answer 1

使用它来获得每个类的准确性:

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


class Metrics(keras.callbacks.Callback):
    def on_train_begin(self, logs={}):
        self._data = []

    def on_epoch_end(self, batch, logs={}):
        x_test, y_test = self.validation_data[0], self.validation_data[1]
        y_predict = np.asarray(model.predict(x_test))

        true = np.argmax(y_test, axis=1)
        pred = np.argmax(y_predict, axis=1)
        
        cm = confusion_matrix(true, pred)
        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
        self._data.append({
            'classLevelaccuracy':cm.diagonal() ,
        })
        return

    def get_data(self):
        return self._data

metrics = Metrics()
history = model.fit(x_train, y_train, epochs=100, validation_data=(x_test, y_test), callbacks=[metrics])
metrics.get_data()

您可以在指标类中更改代码。随心所欲..并且这个工作。你只需使用 metrics.get_data() 获取所有信息..