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Class mean vector component and discriminant analysis
- Source :
- Pattern Recognition Letters, Iosifidis, A 2020, ' Class mean vector component and discriminant analysis ', Pattern Recognition Letters, vol. 140, pp. 207-213 . https://doi.org/10.1016/j.patrec.2020.10.014
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Abstract
- The kernel matrix used in kernel methods encodes all the information required for solving complex nonlinear problems defined on data representations in the input space using simple, but implicitly defined, solutions. Spectral analysis on the kernel matrix defines an explicit nonlinear mapping of the input data representations to a subspace of the kernel space, which can be used for directly applying linear methods. However, the selection of the kernel subspace is crucial for the performance of the proceeding processing steps. In this paper, we propose a component analysis method for kernel-based dimensionality reduction that optimally preserves the pair-wise distances of the class means in the feature space. We provide extensive analysis on the connection of the proposed criterion to those used in kernel principal component analysis and kernel discriminant analysis, leading to a discriminant analysis version of the proposed method. Our analysis also provides more insights on the properties of the feature spaces obtained by applying these methods.<br />8 pages, 2 figures, 2 tables
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
Feature vector
Principal component analysis
Kernel discriminant analysis
Machine Learning (stat.ML)
02 engineering and technology
01 natural sciences
Kernel principal component analysis
Machine Learning (cs.LG)
Kernel (linear algebra)
Artificial Intelligence
Simple (abstract algebra)
Statistics - Machine Learning
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
010306 general physics
Dimensionality reduction
Linear discriminant analysis
Kernel subspace learning
Approximate kernel subspace learning
Kernel method
Signal Processing
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Kernel Fisher discriminant analysis
Algorithm
Software
Subspace topology
Subjects
Details
- Language :
- English
- ISSN :
- 01678655
- Volume :
- 140
- Database :
- OpenAIRE
- Journal :
- Pattern Recognition Letters
- Accession number :
- edsair.doi.dedup.....b5c60fed93a2d07dc5598f2766681326
- Full Text :
- https://doi.org/10.1016/j.patrec.2020.10.014