APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS

APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS

Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. Multi-Output Machine Learning is essential as a decision support tool because decision-mak...

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Bibliographic Details
Main Authors: Karin Joan, Robyn Irawan, Benny Yong
Format: Article
Language:English
Published: Universitas Pattimura 2025-04-01
Series:Barekeng
Subjects:
logistic regression
multi-output machine learning
multivariate regression tree
multivariate random forest
multi-output neural network
Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/16374
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