Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 13 April 2024 / Approved: 15 April 2024 / Online: 16 April 2024 (07:37:52 CEST)

A peer-reviewed article of this Preprint also exists.

Olaniran, O.R.; Alzahrani, A.R.R.; Alzahrani, M.R. Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation. Mathematics 2024, 12, 1425. Olaniran, O.R.; Alzahrani, A.R.R.; Alzahrani, M.R. Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation. Mathematics 2024, 12, 1425.

Abstract

In this paper, we derive the distribution of eigenvalues for a 2×2 random confusion matrix stemming from a machine learning (ML) evaluation problem. Additionally, we present the distributions of both the matrix’s trace and the difference between the two traces of random confusion matrices. We also illustrate the application of these derived distributions in calculating the superiority probability of four baseline ML models.

Keywords

Eigenvalue; Confusion Matrix; Random matrix; Probability distribution; Evaluation metrics

Subject

Computer Science and Mathematics, Probability and Statistics

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