Juliette : 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 ... »

2025-01-02T13:52:08Z

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 ... »

Nouvelle page

=== 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
|
|-
|
| -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)
|
|}

Translations:UC5 : Machine Learning vs DDoS/15/en - Historique des versions