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Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning.
- Source :
-
Discrete Dynamics in Nature & Society . 2/24/2020, p1-5. 5p. - Publication Year :
- 2020
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MACHINE learning
*CLASSIFICATION algorithms
*DISCRIMINANT analysis
*COMMON good
Subjects
Details
- Language :
- English
- ISSN :
- 10260226
- Database :
- Academic Search Index
- Journal :
- Discrete Dynamics in Nature & Society
- Publication Type :
- Academic Journal
- Accession number :
- 141901380
- Full Text :
- https://doi.org/10.1155/2020/1512391