PCA-BASED DATA MINING PROBABILISTIC AND FUZZY APPROACHES WITH APPLICATIONS IN PATTERN RECOGNITION

Luminita State, Catalina Cocianu, Panayiotis Vlamos, Viorica Stefanescu

2006

Abstract

The aim of the paper is to develop a new learning by examples PCA-based algorithm for extracting skeleton information from data to assure both good recognition performances, and generalization capabilities. Here the generalization capabilities are viewed twofold, on one hand to identify the right class for new samples coming from one of the classes taken into account and, on the other hand, to identify the samples coming from a new class. The classes are represented in the measurement/feature space by continuous repartitions, that is the model is given by the family of density functions (fh) hϵH, where H stands for the finite set of hypothesis (classes). The basis of the learning process is represented by samples of possible different sizes coming from the considered classes. The skeleton of each class is given by the principal components obtained for the corresponding sample.

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Paper Citation


in Harvard Style

State L., Cocianu C., Vlamos P. and Stefanescu V. (2006). PCA-BASED DATA MINING PROBABILISTIC AND FUZZY APPROACHES WITH APPLICATIONS IN PATTERN RECOGNITION . In Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-972-8865-69-6, pages 55-60. DOI: 10.5220/0001313500550060


in Bibtex Style

@conference{icsoft06,
author={Luminita State and Catalina Cocianu and Panayiotis Vlamos and Viorica Stefanescu},
title={PCA-BASED DATA MINING PROBABILISTIC AND FUZZY APPROACHES WITH APPLICATIONS IN PATTERN RECOGNITION},
booktitle={Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2006},
pages={55-60},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001313500550060},
isbn={978-972-8865-69-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - PCA-BASED DATA MINING PROBABILISTIC AND FUZZY APPROACHES WITH APPLICATIONS IN PATTERN RECOGNITION
SN - 978-972-8865-69-6
AU - State L.
AU - Cocianu C.
AU - Vlamos P.
AU - Stefanescu V.
PY - 2006
SP - 55
EP - 60
DO - 10.5220/0001313500550060