1.2 KiB
Overview
This folder contains training and inference scripts for two models based on different technologies: MLP (multi-layer perceptron) using scikit-learn and an LSTM-based neural network using TensorFlow. Each model has its own folder with training and testing scripts. Developers interested in DGA detection in nDPI should also visit this folder containing the original ML implementation.
The test scripts only show how to use an already-trained model.
Requirements
To install the necessary dependencies, run
pip install -r requirements.txt
How to use the scripts
1. scikit-learn (MLP model)
Folder: scikit-learn_tests.
Training
To train the MLP model, run the training script:
python scikit-learn_tests/training_script.py
Inference
After training, you can perform inference using the test script:
python scikit-learn_tests/test_script.py
2. TensorFlow (LSTM model)
Folder: tensorflow_tests.
Training
To train the LSTM model, run the training script
python tensorflow_tests/training_script.py
Inference
Once training is complete, you can run inference on the test set with
python tensorflow_tests/test_script.py