##PseUdeep uses the following dependencies:
- Python 3.6
- numpy
- scipy
- scikit-learn
- pandas
##Guiding principles:
**The dataset file contains five datasets, among which NH-990、NS-627、NM-944、H-200、S-200.Among them ,NH-990, NS-627, NM-944 are training datasets,H-200、S-200 are independent testing datasets
**Feature extraction:
- KNFP_feature.py is the implementation of KNFP.
- PNSP_train_feature.py is the implementation of PNSP on the train datasets.
- PNSP_test_feature.py is the implementation of PNSP on the test datasets.
- One_hot_feature.py is the implementation of one-hot encoding.
**Classifier: *PseUdeep.py is the implemention of PseUdeep