Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning
Author
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-24
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
This paper presents a new hybrid discriminant analysis method, and this method combines the ideas of linearity and nonlinearity to establish a two-layer discriminant model.
The first layer is a linear discriminant model, which is mainly used to determine the distinguishable samples and subsample; the second layer is a nonlinear discriminant model, which is used to determine the subsample type.
Numerical experiments on real data sets show that this method performs well compared to other classification algorithms, and its stability is better than the common discriminant models.
American Psychological Association (APA)
Huang, Liwen. 2020. Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-5.
https://search.emarefa.net/detail/BIM-1152833
Modern Language Association (MLA)
Huang, Liwen. Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-5.
https://search.emarefa.net/detail/BIM-1152833
American Medical Association (AMA)
Huang, Liwen. Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-5.
https://search.emarefa.net/detail/BIM-1152833
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152833