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Information 2015, 6(3), 505-521; doi:10.3390/info6030505

News Schemes for Activity Recognition Systems Using PCA-WSVM, ICA-WSVM, and LDA-WSVM

Laboratoire d'Ingénierie des Systèmes Intelligents et Communicants, Faculty of Electronics and Computer Sciences, University of Science and Technology Houari Boumediene (USTHB), 32, El Alia, Bab Ezzouar, 16111 Algiers, Algeria
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Author to whom correspondence should be addressed.
Academic Editor: Ahmed El Oualkadi
Received: 9 June 2015 / Revised: 13 August 2015 / Accepted: 18 August 2015 / Published: 20 August 2015
(This article belongs to the Special Issue Selected Papers from MedICT 2015)
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Abstract

Feature extraction and classification are two key steps for activity recognition in a smart home environment. In this work, we used three methods for feature extraction: Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA). The new features selected by each method are then used as the inputs for a Weighted Support Vector Machines (WSVM) classifier. This classifier is used to handle the problem of imbalanced activity data from the sensor readings. The experiments were implemented on multiple real-world datasets with Conditional Random Fields (CRF), standard Support Vector Machines (SVM), Weighted SVM, and combined methods PCA+WSVM, ICA+WSVM, and LDA+WSVM showed that LDA+WSVM had a higher recognition rate than other methods for activity recognition. View Full-Text
Keywords: activity recognition; principal component analysis; independent component analysis; linear discriminant analysis; weighted support vector machines activity recognition; principal component analysis; independent component analysis; linear discriminant analysis; weighted support vector machines
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Abidine, M.B.; Fergani, B. News Schemes for Activity Recognition Systems Using PCA-WSVM, ICA-WSVM, and LDA-WSVM. Information 2015, 6, 505-521.

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