[1]LIU Zhongbao,WANG Shitong.From Parzen window estimation to feature extraction: a new perspective[J].CAAI Transactions on Intelligent Systems,2012,7(6):471-480.
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From Parzen window estimation to feature extraction: a new perspective

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 6 Page number: 471-480 Column: 综述 Public date: 2012-12-25
Title:
From Parzen window estimation to feature extraction: a new perspective
Author(s):
LIU Zhongbao1; 2;  WANG Shitong1
1. School of Digital Media, Jiangnan University, Wuxi 214122, China;
2. School of Electronics and Computer Science Technology, North University of China, Taiyuan 030051, China
Keywords:
feature extraction;  Parzen window;  density estimation;  data distribution characteristics;  new perspective
CLC:
TP392
DOI:
-
Abstract:
Researches on current feature extraction methods are mainly based on two ways. One originates from geometric properties of highdimensional datasets and attempt to extract fewer features from the original data space according to a certain criterion. The other originates from dimension reduction deviation and try to make the deviation between data before and after dimension reduction be as small as possible. However, there exists almost no study about them from the perspective of the scatter change of a dataset. Based on Parzen window density estimator, we thoroughly revisit the relevant feature extraction methods from a new perspective and the relationships between Parzen window and classical feature extraction methods,ie length of perpendiculars (LPP), linear discriminant analysis (LDA) and principal component analysis (PCA) are built in this paper. Therefore, these feature extraction methods can be researched in the same Parzen window, which provides a new perspective for the research of feature extraction.
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