Project Overview: This project explores Adaptive Boosting (AdaBoost), an ensemble machine learning algorithm that sequentially improves weak classifiers to form a strong classifier. The report ...

Transfer learning, serving as one of the most important research directions in machine learning, has been studied in various fields in recent years. In this paper, we integrate the theory of ...

Here I use three different Machine Learning Classifiers to try classifying the wine dataset, see my report in the readme file The dataset that I used was the Wine Quality Dataset which included a ...

Natras, R., Soja, B. and Schmidt, M. (2022) Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting. Remote Sensing, 14, Article 3547. ...

Credit card fraud detection is a critical problem for any credit card issuing banks. The AdaBoost classifier is used in this study to identify fraudulent transactions. By comparing the proposed ...

Overall, multi-view learning provides a powerful framework for capitalizing on data with multiple informative representations, leading to potentially better machine learning models. Stacked ...

Therefore, these four well-known machine learning algorithms—XGBoost, GB, AdaBoost, and CatBoost—have been chosen for modeling in this study. Furthermore, selected a research topic “the prediction of ...