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Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)
A collection of my practices using the following algorithms: DBSCAN, KNN, Decision Tree Classifier, K-means, Apriori, SMOTE, SVM
This research advances credit card fraud detection by integrating machine learning and deep learning techniques. Key findings include improved model adaptability through hyperparameter tuning.
Supervised Machine Learning and Credit Risk
Data analysis, visualization and prediction to predict whether a patient has benign or malignant breast cancer based on properties of the cancer
Supervised Machine Learning and Credit Risk
Predicting toxicity of molecules. Project on course "Data Mining 2"