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Misclassification analysis of discriminant model

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Abstract

This paper extends the criterion of the misclassification ratio of discriminant model and presents a new selection method of discriminant model. For selecting the discriminant model, this method establishes the rule of misclassification degree ratio through misclassification ratio of the discriminant model and misclassification degree of the samples. To test the effect of this method, this work uses seven UCI data sets. Numerical experiments on these examples indicate that this method has certain rationality and has a better effect to select a discriminant model.

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Authors and Affiliations

  1. College of Mathematics and Computer science, Quanzhou Normal University, Quanzhou, 362000, China

    Li-wen Huang

  2. Key Laboratory of Financial Mathematics, Putian University, Putian, 351100, China

    Li-wen Huang

Authors
  1. Li-wen Huang
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Correspondence to Li-wen Huang.

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The authors declare no conflict of interest.

Supported by the National Natural Science Foundation of China(52070119) and Key Laboratory of Financial Mathematics of Fujian Province University (Putian University) (JR201801).

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Huang, Lw. Misclassification analysis of discriminant model. Appl. Math. J. Chin. Univ. 38, 180–191 (2023). https://doi.org/10.1007/s11766-023-3823-8

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  • DOI: https://doi.org/10.1007/s11766-023-3823-8

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