« Translations:UC5 : Machine Learning vs DDoS/15/en » : différence entre les versions
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Page créée avec « === Notebooks === {| class="wikitable" |+ !Notebook !Data Science step ! |- |Cyber_unsw_analysis.ipynb |''Data exploration'' | |- |Cyber_unsw_analysisGmm.ipynb |''data exploration for GMM clustering'' | |- |Cyber_unsw_standardization.ipynb |''data standardization'' | |- |Cyber_unsw_autoencoder.ipynb |''Binary classifier study. Half-Supervised Autoencoder modeling, we tested:'' | |- | | -logistic regression | |- | | -Autoencoder Inria like ... » |
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Dernière version du 2 janvier 2025 à 14:52
Notebooks
| Notebook | Data Science step | |
|---|---|---|
| Cyber_unsw_analysis.ipynb | Data exploration | |
| Cyber_unsw_analysisGmm.ipynb | data exploration for GMM clustering | |
| Cyber_unsw_standardization.ipynb | data standardization | |
| Cyber_unsw_autoencoder.ipynb | Binary classifier study. Half-Supervised Autoencoder modeling, we tested: | |
| -logistic regression | ||
| -Autoencoder Inria like | ||
| -Autoencoder single layer | ||
| -Autoencoder multi layers | ||
| Cyber_unsw_complete_analysis.ipynb | data exploration | |
| Cyber_unsw_model.ipynb | Data Supervised model, to classify attacks of different kinds, we tested: | |
| -Random Forest Classifier (rfc) | ||
| -Support Vector Classification (svm) | ||
| -Multi-Layer Perceptron (mlp) | ||
| -Artificial Neural Network (ann) | ||
| -eXtreme Gradient Boosting (xgb) | ||
| -Convolutional Neural Network (cnn) |
