An extension of XGBoost to probabilistic modelling
Code for paper "Copula-based conformal prediction for Multi-Target Regression"
A Multi-Output Regression Framework in Python
An extension of Py-Boost to probabilistic modelling
🌳MultiLGBM🌳: A simple multi-objective regression example to show how to trade-off objectives on the Pareto front with a single LGBM model.
A machine learning library for regression, which implements a new formulation of gradient boosting.
Predict the net rate of bike renting
A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules
A simple parameter reconstruction workflow using well-established machine learning algorithms and neural networks. The workflow is implemented and explained step-by-step in a Jupyter notebook.
자율주행 센서의 안테나 성능 예측 AI 경진대회, LG AI Research (2022.08.01 ~ 2022.08.26)
Final Rank - 81 out of 5060
A multi-target regression algorithm based on Gaussian process regression
Kr8cht study-choice project: multi-target regression (MTR) on Dutch activity descriptions to predict eight curricular domain scores and six RIASEC traits. Includes code and artifacts for the ACM SAC 2026 Artificial Intelligence for Education track
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