How vijay9972/ncifa_ndn works
This repository is a notebook-based experimentation toolkit for generating and evaluating network-feature data with FeatureGAN, other GANs, and traditional methods. The visible stages span preprocessing, training, generation or data preparation, and evaluation/validation. The tree also includes result and validation artifacts. With no README or sampled notebook code, the connections between stages and their data inputs/outputs cannot be verified, so the graph shows the researcher entry points without implying a pipeline.
Main entry points: featureGAN_preprocessing.ipynb Preprocess · featureGAN_train.ipynb Train · featureGAN_generate.ipynb Generate · featureGAN_evaluate.ipynb Evaluate
Components 20
FeatureGAN workflow
- Preprocess
Fagan/featureGAN_preprocessing.ipynb - Train
Fagan/featureGAN_train.ipynb - Generate
Fagan/featureGAN_generate.ipynb - Evaluate
Fagan/featureGAN_evaluate.ipynb - Validate
Fagan/Step_7_featureGAN_validate.ipynb - FeatureGAN results
results/fagan - FeatureGAN validation
Fagan/validation_results
GAN workflow
- Preprocess
Gan/preprocessing_gans.ipynb - Train
Gan/train_gans.ipynb - Generate data
Gan/generate_gandatas.ipynb - Evaluate
Gan/evaluate_gans.ipynb - GAN results
results/gan
Traditional methods
- Generate data
traditional/Data_generation_traditional1.ipynb - Preprocess
traditional/preprocessing_traditional.ipynb - Train methods
traditional/train_traditional_methods.ipynb - Compare methods
traditional/result_traditional_methods.ipynb - Imbalance summary
traditional/imbalance_ratio_summary.csv - Traditional results
results/traditional
Validation artifacts
- Validation metrics
validation_results
Other components
- Researcher
Connections 13
- Researcher → Preprocess: opens
- Researcher → Train: opens
- Researcher → Generate: opens
- Researcher → Evaluate: opens
- Researcher → Validate: opens
- Researcher → Preprocess: opens
- Researcher → Train: opens
- Researcher → Generate data: opens
- Researcher → Evaluate: opens
- Researcher → Generate data: opens
- Researcher → Preprocess: opens
- Researcher → Train methods: opens
- Researcher → Compare methods: opens