如何绘制训练误差和验证误差与时期数的关系图？

Question

如何绘制训练误差和验证误差与轮数的关系？


train_data = generate_arrays_for_training(indexPat, filesPath, end=75)
validation_data=generate_arrays_for_training(indexPat, filesPath, start=75)
            model.fit_generator(generate_arrays_for_training(indexPat, filesPath, end=75), #end=75),#It take the first 75%
                                validation_data=generate_arrays_for_training(indexPat, filesPath, start=75),#start=75), #It take the last 25%
                                #steps_per_epoch=10000, epochs=10)
                                steps_per_epoch=int((len(filesPath)-int(len(filesPath)/100*25))),#*25), 
                                validation_steps=int((len(filesPath)-int(len(filesPath)/100*75))),#*75),
                                verbose=2,
                                epochs=300, max_queue_size=2, shuffle=True, callbacks=[callback])

Answer 1

这可能是您要查找的内容，但您应该提供更多详细信息以获得更合适的答案

import matplotlib.pyplot as plt

hist = model.fit_generator(...)

plt.figure()
plt.plot(hist.history['loss'])
plt.plot(hist.history['val_loss'])
plt.title('model loss')
plt.ylabel('loss')
plt.xlabel('epoch')
plt.legend(['train','val'], loc = 'upper left')
plt.show()

如何绘制训练误差和验证误差与时期数的关系图？

how to plot training error and validation error vs number of epochs?

python

validation

training-data

deep-learning

conv-neural-network