Deducing of Optimal Machine Learning Algorithms for Heterogeneity

• URL: http://arxiv.org/abs/2111.05558v1
• Date: Wed, 10 Nov 2021 07:55:26 GMT
• Title: Deducing of Optimal Machine Learning Algorithms for Heterogeneity
• Authors: Omar Alfarisi, Zeyar Aung and Mohamed Sassi
• Abstract summary: This paper describes the optimal among the best of the algorithms. We built a synthetic data set and performed the supervised machine learning runs for five different algorithms.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: For defining the optimal machine learning algorithm, the decision was not easy for which we shall choose. To help future researchers, we describe in this paper the optimal among the best of the algorithms. We built a synthetic data set and performed the supervised machine learning runs for five different algorithms. For heterogeneity, we identified Random Forest, among others, to be the best algorithm.

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