如何提高这个 CNN 模型的准确率?
tensorflow 554
原文标题 :How to increase the accuracy of this CNN Model?
我在这个模型的值中尝试了许多组合。
- 在以下情况下可以使用 2D 卷积代替 1D 吗?
- 如何提高训练数据集的准确性?
原始数据集的形状:(343889, 80)
训练数据集的形状:(257916、80)
形状-培训标签:(257916,)
测试数据集的形状:(85973、80)
形状 – 测试标签:(85973,)
模型是
inputShape = (80,1,)
model = Sequential()
model.add(Input(shape=inputShape))
model.add(Conv1D(filters=80, kernel_size=30, activation='relu'))
model.add(MaxPooling1D(40))
model.add(Dense(60))
model.add(Dense(9))
model.compile(optimizer='adam', loss='binary_crossentropy',
metrics=['accuracy'])
模型总结
Model: "sequential_11"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv1d_11 (Conv1D) (None, 51, 80) 2480
max_pooling1d_9 (MaxPooling (None, 1, 80) 0
1D)
dense_8 (Dense) (None, 1, 60) 4860
dense_9 (Dense) (None, 1, 9) 549
=================================================================
Total params: 7,889
Trainable params: 7,889
Non-trainable params: 0
_________________________________________________________________
培训如下。
Epoch 1/5
8060/8060 [==============================] - 56s 7ms/step - loss: -25.7724 - accuracy: 0.0015
Epoch 2/5
8060/8060 [==============================] - 44s 5ms/step - loss: -26.7578 - accuracy: 0.0011
Epoch 3/5
8060/8060 [==============================] - 43s 5ms/step - loss: -26.7578 - accuracy: 0.0011