DocumentCode
458877
Title
Particle Swarm Optimized Polynomials for Data Classification
Author
Bijan Bihari Misra ; Suresh Chandra Satapathy ; Dash, P.K.
Author_Institution
Dept. of Comput. Sci., Coll. of Eng. Bhubaneswar
Volume
1
fYear
2006
fDate
16-18 Oct. 2006
Firstpage
649
Lastpage
654
Abstract
Data classification is an important area of data mining. Several well known techniques such as decision tree, neural network, etc. are available for this task. In this paper we propose a particle swarm optimized polynomial equation for classification of several well known data sets. Our proposed method is derived from some of the findings of the valuable information like number of terms, number and combination of features in each term, degree of the polynomial equation etc. of our earlier work on data classification using polynomial neural network. The PSO optimizes these polynomial equations. The polynomial equation that gives the best performance is considered as the model for classification. Our simulation result shows that the proposed approach is able to give competitive classification accuracy compared to PNN in many datasets
Keywords
data handling; data mining; neural nets; particle swarm optimisation; pattern classification; data classification; data handling; data mining; particle swarm optimized polynomials; polynomial equation; polynomial neural network; Data engineering; Data handling; Decision trees; Educational institutions; Equations; Input variables; Neural networks; Particle swarm optimization; Pattern recognition; Polynomials; Group Methods Of Data Handling; Particle Swarm Optimization; Polynomial Neural Network;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location
Jinan
Print_ISBN
0-7695-2528-8
Type
conf
DOI
10.1109/ISDA.2006.214
Filename
4021516
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