Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation

Oyebayo Ridwan Olaniran (), Ali Rashash R. Alzahrani and Mohammed R. Alzahrani
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Oyebayo Ridwan Olaniran: Department of Statistics, Faculty of Physical Sciences, University of Ilorin, llorin 1515, Nigeria
Ali Rashash R. Alzahrani: Mathematics Department, Faculty of Sciences, Umm Al-Qura University, Makkah 24382, Saudi Arabia
Mohammed R. Alzahrani: Department of Psychology, Faculty of Education, Umm Al-Qura University, Al-Abidiyah, Makkah 24382, Saudi Arabia

Mathematics, 2024, vol. 12, issue 10, 1-14

Abstract: This paper examines the distribution of eigenvalues for a 2 × 2 random confusion matrix used in machine learning evaluation. We also analyze the distributions of the matrix’s trace and the difference between the traces of random confusion matrices. Furthermore, we demonstrate how these distributions can be applied to calculate the superiority probability of machine learning models. By way of example, we use the superiority probability to compare the accuracy of four disease outcomes machine learning prediction tasks.

Keywords: eigenvalue; confusion matrix; random matrix; probability distribution; evaluation metrics (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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