Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification

Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification

Machine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. HDI serves as a key indicator of regional development progress, making it crucial to classify HDI categories at the...

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Bibliographic Details
Main Authors: Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah
Format: Article
Language:English
Published: Department of Mathematics, Universitas Negeri Gorontalo 2025-02-01
Series:Jambura Journal of Mathematics
Subjects:
classification
random forest
xgboost
lightgbm
human development index
Online Access:https://ejurnal.ung.ac.id/index.php/jjom/article/view/28290
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