Decision Tree Learning. As discussed in the last lecture, the representation scheme we choose to represent our learned solutions and the way in which we learn those solutions are the most important ...

but we also want a decision tree that generalizes well to new examples, i.e. we would like the decision tree to give the right answer on new examples it has never seen before so we want to avoid ...

This study aims to design a machine learning model to predict drug addiction. The dataset includes various demographic, psychosocial, and behavioral factors contributing to drug addiction. The ...

It proposed three intrusion detection systems by implementing many machine learning algorithms, including tree-based algorithms (decision tree, random forest, XGBoost, LightGBM, CatBoost etc.), ...

Development of urban intelligent cities introduces a severe rise in environmental pollution, ranging from air and water pollution to noise pollution. Explicitly, the upsurge in deforestation, ...

This repository proposed three intrusion detection systems by implementing many machine learning algorithms, including tree-based algorithms (decision tree, random forest, XGBoost, LightGBM, CatBoost ...