用Python解释Keras神经网络的准确性

Question

我创建了Keras神经网络。在八个时间段内对神经网络进行了训练，它输出了此损失值和准确性：

Epoch 1/8
2009/2009 [==============================] - 0s 177us/step - loss: 0.0824 - acc: 4.9776e-04
Epoch 2/8
2009/2009 [==============================] - 0s 34us/step - loss: 0.0080 - acc: 4.9776e-04
Epoch 3/8
2009/2009 [==============================] - 0s 37us/step - loss: 0.0071 - acc: 4.9776e-04
Epoch 4/8
2009/2009 [==============================] - 0s 38us/step - loss: 0.0071 - acc: 4.9776e-04
Epoch 5/8
2009/2009 [==============================] - 0s 35us/step - loss: 0.0070 - acc: 4.9776e-04
Epoch 6/8
2009/2009 [==============================] - 0s 38us/step - loss: 0.0071 - acc: 4.9776e-04
Epoch 7/8
2009/2009 [==============================] - 0s 36us/step - loss: 0.0068 - acc: 4.9776e-04
Epoch 8/8
2009/2009 [==============================] - 0s 40us/step - loss: 0.0070 - acc: 4.9776e-04

我如何解释这些精确性？我知道减少损耗是一个好兆头，但是我可以从中得出任何直接的准确度指标，例如“我的结果是……。”准确度是82％还是23％？

Answer 1

根据您的问题是二进制分类还是多分类分类，您的准确度计算方式类似于Binary Accuracy或Categorical accuracy。