Factors of Income: A Machine Learning Analysis
A machine learning analysis of US Census salary data aiming to predict income levels based on critical variables like marital status, age, and capital gains. The study explores XGBoost as a powerful algorithm for predicting annual income thresholds, with potential applications in analyzing the econo
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Understanding Gradient Boosting and XGBoost in Decision Trees
Dive into the world of Gradient Boosting and XGBoost techniques with a focus on Decision Trees, their applications, optimization, and training methods. Explore the significance of parameter tuning and training with samples to enhance your machine learning skills. Access resources to deepen your unde
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Enhancing Student Success Prediction Using XGBoost
There is a growing concern about academic performance in higher education institutions. This project aims to predict student dropout and success using XGBoost, focusing on early identification of at-risk students to provide personalized support. Leveraging data from Polytechnic Institute of Portaleg
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Machine Learning Applications for EBIS Beam Intensity and RHIC Luminosity Maximization
This presentation discusses the application of machine learning for optimizing EBIS beam intensity and RHIC luminosity. It covers topics such as motivation, EBIS beam intensity optimization, luminosity optimization, and outlines the plan and summary of the project. Collaborators from MSU, LBNL, and
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