DocumentCode
1869039
Title
Evolutionary nonlinear data transformation for visualization and classification tasks
Author
Zabkiewicz, Kamil
Author_Institution
Inst. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania
fYear
2013
fDate
8-11 Sept. 2013
Firstpage
683
Lastpage
685
Abstract
In this paper we propose new approach in data set dimensionality reduction. We use classical principal component analysis transformation. Instead of rejecting features we generate new one by using nonlinear feature transformation. The values of transformation weights are changed evolutionary by using genetic algorithms. Results show better classification rates in smaller feature space. Visualization results also look better.
Keywords
data reduction; data visualisation; feature extraction; genetic algorithms; pattern classification; principal component analysis; classical principal component analysis transformation; classification rate; classification task; data set dimensionality reduction; evolutionary nonlinear data transformation; feature generation; feature space; genetic algorithm; nonlinear feature transformation; transformation weight values; visualization task; Data visualization; Educational institutions; Electronic mail; Glass; Heart; Principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
Conference_Location
Krako??w
Type
conf
Filename
6644080
Link To Document