Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
This repository contains the work done on the implementation and testing of three different fair machine learning algorithms based on decision trees for binary classification with one binary sensitive ...
ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Effect of incorporating symptom burden with mortality as a composite outcome on accuracy and bias in palliative care identification algorithms in oncology. This is an ASCO Meeting Abstract from the ...
Municipal Solid Waste Generation (MSWG) presents a significant challenge for sustainable urban development, with waste production escalating at alarming rates worldwide. To address this issue, ...
LightGBM is a sophisticated, open-source, tree-based system that was introduced in 2017. LightGBM can perform binary classification , multi-class classification, (predict one of three or more possible ...
Wrapping Up The LightGBM system was inspired by the XGBoost (extreme gradient boosting) system, which in turn was inspired by earlier tree boosting algorithms. The "boosting" term of the LightGBM name ...
Abstract: This paper introduces a data-driven approach employing the Light Gradient Boosting Machine (LightGBM) algorithm as a controller for robotic manipulators. By harnessing data-driven techniques ...
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