Vinayakumar Ravi

Now it is giving different error when i tried to run the sudo python train.py data/processed.h5 model.h5 --epochs 20 Using Theano backend. Traceback (most recent call last): File "train.py", line...

Yes, I had corrected. I think you are using data and label as same in both train and test (in train.py line n0=54). Why? Also, you are giving the testing...

Getting an error, when I tried to run python preprocess.py data/smiles_500k.h5 data/processed_500.h5 File "preprocess.py", line 85, in main() File "preprocess.py", line 72, in main apply_fn=lambda ch: np.array(map(one_hot_encoded_fn, File "preprocess.py", line...

Just replace each term with an unique number.

The datasets are publically available. These are standard datasets used for network intrusion detection and I don't think I have the permission to upload other datasets.

Yes, both are same. The same code (all.py) can be used for both binary and multiclass classification.

The data should be converted to numeric and then you can use my code. For example, in the data set 'tcp' should be replace by numeric

Details available in https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html

Here, the data is converted into 3 dimension (tensor format)