XGBoost Projects for ME, MTech, Masters, MS abroad, and PhD students. These XGBoost ieee projects are implemented with future work and extension for final year students with research paper writing and publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest XGBoost Projects
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A Hybrid Approach for Forecasting Occupancy of Buildings Multiple Space Types
This project focuses on predicting how many people are present in different rooms of a university building. It uses data from indoor and outdoor sensors, energy usage, and Wi-Fi connections to make predictions. By using smart machine learning models, it helps improve energy management and space use. The proposed method gives more accurate results than other approaches. -
A Semi-Supervised Learning Approach to Quality-Based Web Service Classification
This project focuses on helping users choose the best web service by using machine learning. It introduces a smart system that can learn even when only a small amount of data is labeled. The system automatically classifies and ranks services based on quality. As a result, it improves accuracy and performance compared to traditional methods.
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