DNN-Ensemble IDS is a machine learning based classification model for intrusion detection exploiting ensembles of classifiers.
This project uses predictive modeling techniques to identify fraudulent Credit Card transactions on data obtained from European credit card holders made in September 2013.
Testing AutoNovel and UNO novel-class-discovery techniques to assess their prerformances under different settings. Plot of tSNE to evaluate clustering capabilities for known and new classes
Expérimentations sur divers modèles et méthodes de Machine Learning pour la classification de textes, et étude des mesures d'évaluation des modèles après normalisation des données
Opportunities and challenges in partitioning the graph measure space of real-world networks
Practical works on machine learning course at university
Resampling techniques to use on modeling train/test/validation data splits
Projeto de Machine Learning para detecção de fraudes em bases desbalanceadas.
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