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Comparison of Different Dichotomous Classification Algorithms

Yu. I. Zhuravlev, V. V. Ryazanov, Vl. V. Ryazanov, Levon Aslanyan, Hasmik Sahakyan

2020Pattern Recognition and Image Analysis17 citationsDOI

Abstract

Experimental investigations of various dichotomous classification algorithms are carried out. Dichotomous classification, or Error-Correcting Output Codes (ECOCs) classification, is based on the construction of a binary code matrix. The rows of the matrix contain unique codewords of classes, and columns are called dichotomies. A dichotomous classification consists of two stages: coding (construction of a code matrix) and decoding, making a decision on the correspondence of an object to a class by analyzing the code matrix. In this study, an experimental comparison of newly proposed methods for constructing dichotomies and a comparison of different approaches to decoding by the available code matrix are proposed. Preliminary experiments show the prospects of proposed methods.

Topics & Concepts

Decoding methodsRowParity-check matrixDichotomyComputer scienceMatrix (chemical analysis)AlgorithmClass (philosophy)Code (set theory)Coding (social sciences)Pattern recognition (psychology)Logical matrixNull (SQL)MathematicsArtificial intelligenceLow-density parity-check codeData miningStatisticsProgramming languageGroup (periodic table)Materials scienceComposite materialChemistryOrganic chemistrySet (abstract data type)Imbalanced Data Classification TechniquesMachine Learning and Data ClassificationAnomaly Detection Techniques and Applications