深度学习--绘制模型训练曲线_三分类变量模型的训练曲线

模型训练完成后，我们需要绘制训练过程中的精度和损失函数变换曲线，这里将训练和验证集的训练曲线绘制封装成一个函数，在模型训练完成后可以直接调用。

import matplotlib.pyplot as plt
# define the function
def training_plot(model_name):
    loss = model_name.history['loss']
    val_loss = model_name.history['val_loss']
    acc = model_name.history['acc']
    val_acc = model_name.history['val_acc']

    # make a figure
    fig = plt.figure(figsize=(8,4))
    # subplot loss
    fig1 = fig.add_subplot(121)    # 一行两列第一个
    fig1.plot(loss,label='train_loss')
    fig1.plot(val_loss,label='val_loss')
    fig1.set_xlabel('Epochs')
    fig1.set_ylabel('Loss')
    fig1.set_title('Loss on Training and Validation Data')
    fig1.legend()

	plt.subplot(211)
    plt.plot(model_trained.history['acc'])
    plt.plot(model_trained.history['val_acc'])
    plt.title('Model Accuracy')
    plt.ylabel('Accuracy&#
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