如何使用keras创建CNN模型?
How to create CNN model using keras?
我想创建一个包含所有 nSeizures 模型的 CNN 模型,而不是为每个癫痫文件创建模型,但我收到此错误 。
for i in range(0, nSeizure):
print(nSeizure)
print('SEIZURE OUT: '+str(i+1))
print('Training start')
## create model
model = createModel()
filesPath=getFilesPathWithoutSeizure(i, indexPat)
## create one model including all nSeizures models
for model in range(0, nSeizure):
mylist.append(model)
data=mylist.append(model)
history=data.fit_generator(generate_arrays_for_training(indexPat, filesPath, end=75),
validation_data=generate_arrays_for_training(indexPat, filesPath,
start=75),
#steps_per_epoch=10000, epochs=10)
steps_per_epoch=int((len(filesPath)-int(len(filesPath)/100*25))),
validation_steps=int((len(filesPath)-int(len(filesPath)/100*75))),
verbose=2,
epochs=300, max_queue_size=2, shuffle=True, callbacks=[callback])
mylist.append(model)
returnsNone。
当你调用 data.fit_generator
时,它实际上意味着 None.fit_generator
。
考虑重写代码。
我想创建一个包含所有 nSeizures 模型的 CNN 模型,而不是为每个癫痫文件创建模型,但我收到此错误
for i in range(0, nSeizure):
print(nSeizure)
print('SEIZURE OUT: '+str(i+1))
print('Training start')
## create model
model = createModel()
filesPath=getFilesPathWithoutSeizure(i, indexPat)
## create one model including all nSeizures models
for model in range(0, nSeizure):
mylist.append(model)
data=mylist.append(model)
history=data.fit_generator(generate_arrays_for_training(indexPat, filesPath, end=75),
validation_data=generate_arrays_for_training(indexPat, filesPath,
start=75),
#steps_per_epoch=10000, epochs=10)
steps_per_epoch=int((len(filesPath)-int(len(filesPath)/100*25))),
validation_steps=int((len(filesPath)-int(len(filesPath)/100*75))),
verbose=2,
epochs=300, max_queue_size=2, shuffle=True, callbacks=[callback])
mylist.append(model)
returnsNone。
当你调用 data.fit_generator
时,它实际上意味着 None.fit_generator
。
考虑重写代码。