✦ LIBER ✦

Correlative components analysis for pattern classification

✍ Scribed by Dezhao Chen; Yaqiu Chen; Shangxu Hu

Publisher: Elsevier Science
Year: 1996
Tongue: English
Weight: 575 KB
Volume: 35
Category: Article
ISSN: 0169-7439
DOI: 10.1016/s0169-7439(96)00033-0

No coin nor oath required. For personal study only.

✦ Synopsis

Based upon a novel method named correlative components analysis, a simple but efficient pattern classification technique is proposed in this paper. Using this method, the relatively important components of high-dimensional pattern can be successfully identified, the original problem will be mapped onto a lower dimensional space, and therefore the complexity of a high-dimensional pattern classification problem will be substantially reduced. For comparing with the methods of sequential discriminant analysis and the principal component analysis, an example of classifying complex chemical information was used, and the results verified that the new method is reasonable in principle and successful in practice.

📜 SIMILAR VOLUMES

Multivariate analysis for pattern classi

Multivariate analysis for pattern classification

✍ J.R. Riba; A. Carnicer; S. Vallmitjana; I. Juvells 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 58 KB

Analysis of evidence-theoretic decision

Analysis of evidence-theoretic decision rules for pattern classification

✍ Thierry Denoeux 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 862 KB

The Dempster-Shafer theory provides a convenient framework for decision making based on very limited or weak information. Such situations typically arise in pattern recognition problems when patterns have to be classified based on a small number of training vectors, or when the training set does not

Interclass analysis in symbolic pattern

Interclass analysis in symbolic pattern classification problems

✍ Manabu Ichino; Shinya Ishikawa 📂 Article 📅 2006 🏛 Springer 🌐 English ⚖ 648 KB

Fuzzy convex set-based pattern classific

Fuzzy convex set-based pattern classification for analysis of mammographic microcalcifications

✍ Wojciech M. Grohman; Atam P. Dhawan 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 468 KB

There are many di!erent criteria for the comparative analysis of pattern classi"ers. They include generalization ability, computational complexity and understanding of the feature space. In some applications such as the medical diagnostic systems it is crucial to use reliable tools, whose behavior i

Filter-based models for pattern classifi

Filter-based models for pattern classification

✍ Terry M. Caelli; Walter F. Bischof; Zhi-Qiang Liu 📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 732 KB

Self-generating prototypes for pattern c

Self-generating prototypes for pattern classification

✍ Hatem A. Fayed; Sherif R. Hashem; Amir F. Atiya 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 644 KB