Modified principal component analysis: An integration of multiple similarity subspace models

Zizhu Fan, Yong Xu, Wangmeng Zuo, Jian Yang, Jinhui Tang, Zhihui Lai, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

53 Citations (Scopus)

Abstract

We modify the conventional principal component analysis (PCA) and propose a novel subspace learning framework, modified PCA (MPCA), using multiple similarity measurements. MPCA computes three similarity matrices exploiting the similarity measurements: 1) mutual information; 2) angle information; and 3) Gaussian kernel similarity. We employ the eigenvectors of similarity matrices to produce new subspaces, referred to as similarity subspaces. A new integrated similarity subspace is then generated using a novel feature selection approach. This approach needs to construct a kind of vector set, termed weak machine cell (WMC), which contains an appropriate number of the eigenvectors spanning the similarity subspaces. Combining the wrapper method and the forward selection scheme, MPCA selects a WMC at a time that has a powerful discriminative capability to classify samples. MPCA is very suitable for the application scenarios in which the number of the training samples is less than the data dimensionality. MPCA outperforms the other state-of-the-art PCA-based methods in terms of both classification accuracy and clustering result. In addition, MPCA can be applied to face image reconstruction. MPCA can use other types of similarity measurements. Extensive experiments on many popular real-world data sets, such as face databases, show that MPCA achieves desirable classification results, as well as has a powerful capability to represent data.
Original languageEnglish
Article number6701361
Pages (from-to)1538-1552
Number of pages15
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume25
Issue number8
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Feature extraction
  • modified principal component analysis (MPCA)
  • similarity measurement
  • similarity subspace
  • weak machine cell (WMC)

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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