莫烦keras学习自修第四天【分类问题】

1.代码实战

#!/usr/bin/env python
#! _*_ coding:UTF-8 _*_

# 导入numpy
import numpy as np
np.random.seed(1337)
# 导入验证码图片数据集
from keras.datasets import mnist
from keras.utils import np_utils
# 导入kearas的模型
from keras.models import Sequential
# 导入keras的层和激励函数
from keras.layers import Dense, Activation
# 导入keras的优化器
from keras.optimizers import RMSprop

(X_train, y_train), (X_test, y_test) = mnist.load_data()

# 生成训练数据和测试数据
X_train = X_train.reshape(X_train.shape[0], -1) / 255.
X_test = X_test.reshape(X_test.shape[0], -1) / 255.
y_train = np_utils.to_categorical(y_train, num_classes=10)
y_test = np_utils.to_categorical(y_test, num_classes=10)

# 生成训练模型，传入每个层及激励函数构造训练模型
model = Sequential([
    Dense(32, input_dim=784),
    Activation('relu'),
    Dense(10),
    Activation('softmax'),
])

# 自定义优化器
rmsprop = RMSprop(lr=0.001, rho=0.9, epsilon=1e-08, decay=0.0)

# 使用优化器，和误差函数等编译训练模型
model.compile(optimizer=rmsprop,
              loss='categorical_crossentropy',
              metrics=['accuracy'])

# 开始训练神经网络
model.fit(X_train, y_train, epochs=2, batch_size=32)

# 开始测试神经网络
loss, accuracy = model.evaluate(X_test, y_test)

print('test loss: ', loss)
print('test accuracy: ', accuracy)

结果：

/Users/liudaoqiang/PycharmProjects/numpy/venv/bin/python /Users/liudaoqiang/Project/python_project/keras_day03/classifier.py
Using Theano backend.
Downloading data from https://s3.amazonaws.com/img-datasets/mnist.npz

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('test loss: ', 0.18316557179167867)
('test accuracy: ', 0.9466)

Process finished with exit code 0

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