IMDEA Networks Institute Publications Repository

Relevant Feature Selection and Generation in High Dimensional Haptic-based Biometric Data

Sakr, Nizar and Alsulaiman, Fawaz and Valdés, Julio and El Saddik, Abdulmotaleb and Georganas, Nicolas (2009) Relevant Feature Selection and Generation in High Dimensional Haptic-based Biometric Data. In: The 5th International Conference on Data Mining (DMIN 09), 13-16 July, 2009, Las Vegas, Nevada, USA.

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In this paper, a study is conducted in order to explore the use of genetic programming, in particular gene expression programming (GEP), in finding analytic functions that can behave as classifiers in high-dimensional haptic feature spaces. More importantly, the determined explicit functions are used in discovering minimal knowledge-preserving subsets of features from very high dimensional haptic datasets, thus acting as general dimensionality reducers. This approach is applied to the haptic-based biometrics problem; namely, in user identity verification. GEP models are initially generated using the original haptic biometric datatset, which is imbalanced in terms of the number of representative instances of each class. This procedure was repeated while considering an undersampled (balanced) version of the datasets. The results demonstrated that for all datasets, whether imbalanced or undersampled, a certain number (on average) of perfect classification models were determined. In addition, using GEP, great feature reduction was achieved as the generated analytic functions (classifiers) exploited only a small fraction of the available features.

Item Type: Conference or Workshop Papers (Paper)
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Systems Ad Systems Administrator
Date Deposited: 14 Feb 2012 16:37
Last Modified: 06 Apr 2018 15:47

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