keras做图像2分类，lr=0.000000001，optimizer是rmsprop，batch size=32，y_pred>0.1定义为正
第一次跑的结果,：
Epoch 1/5
81/81 [==============================] - 1s 8ms/step - loss: 14.5646 - acc: 0.0864
Epoch 2/5
81/81 [==============================] - 0s 6ms/step - loss: 14.5646 - acc: 0.0864
Epoch 3/5
81/81 [==============================] - 0s 6ms/step - loss: 14.5646 - acc: 0.0864
Epoch 4/5
81/81 [==============================] - 0s 5ms/step - loss: 14.5646 - acc: 0.0864
Epoch 5/5
81/81 [==============================] - 0s 6ms/step - loss: 14.5646 - acc: 0.0864
混淆矩阵：
[[ 0 36]
[ 0 3]]
第2次跑的结果：
Epoch 1/5
81/81 [==============================] - 1s 7ms/step - loss: 3.4956 - acc: 0.4074
Epoch 2/5
81/81 [==============================] - 1s 7ms/step - loss: 1.3929 - acc: 0.9136
Epoch 3/5
81/81 [==============================] - 1s 6ms/step - loss: 1.3929 - acc: 0.9136
Epoch 4/5
81/81 [==============================] - 0s 5ms/step - loss: 1.3929 - acc: 0.9136
Epoch 5/5
81/81 [==============================] - 0s 5ms/step - loss: 1.3929 - acc: 0.9136
混淆矩阵
[[36 0]
[ 3 0]]
2次跑的结果差距这么大的原因？
