razor08 / efficient-cnn-bilstm-for-network-ids Goto Github PK

ypeError Traceback (most recent call last)
in ()
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---> 31 model.fit(x_train_1, y_train_1,validation_data=(x_test_2,y_test_2), epochs=2)
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33 pred = model.predict(x_test_2)

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds)
940 # In this case we have created variables on the first call, so we run the
941 # defunned version which is guaranteed to never create variables.
--> 942 return self._stateless_fn(*args, **kwds) # pylint: disable=not-callable
943 elif self._stateful_fn is not None:
944 # Release the lock early so that multiple threads can perform the call

TypeError: 'NoneType' object is not callable

On which base you are classified the data. I'm not getting how to classify the data??

Hello, your code is to comprehensively process the training set and test set, and then test on the model. The result of this test set will be inconsistent with the original test set. Is the result obtained in this way accurate?

I have been trying to run the program using UNSW-NB15 data set downloaded from the official site, but unfortunately I am stuck here(in the screenshot provided below). Can you kindly help me to figure it out? @razor08

AttributeError: 'Sequential' object has no attribute 'predict_classes'

how to fix this error

your code miss some part in nsl_kdd, can you upgrade it?

how to fix this error: TypeError: ('Keyword argument not understood:', 'pool_length')