Comparative analysis of XLMiner and WEKA for pattern classification

Author

Subbulakshmi, C.V. ; Deepa, S.N. ; Malathi, N.

Author_Institution

EEE Dept., Avinashilingam Univ. for Women, Coimbatore, India

fYear

2012

fDate

23-25 Aug. 2012

Firstpage

453

Lastpage

457

Abstract

This paper presents a comparative analysis of the open source packages XLMiner and WEKA used for pattern classification task. The artificial neural network implemented is multilayer perceptron. The Statlog (heart) dataset from UCI-MLR (University of California, Irvine) was used for analysis. The results of multilayer perceptron against their implementation in WEKA and XLMiner were encouraging and produced valuable information for healthcare organization.

Keywords

data analysis; data mining; health care; mathematical analysis; medical computing; medical information systems; multilayer perceptrons; pattern classification; Irvine; Statlog dataset; UCI-MLR; University of California; WEKA; XLMiner; artificial neural network; data mining; discovery-driven data analysis; healthcare organization; mathematical analysis; multilayer perceptron; open source packages; pattern classification task; Data preprocessing; Data visualization; Heart; IEL; Silicon; Software; System-on-a-chip; Classification; WEKA; XLMiner;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Communication Control and Computing Technologies (ICACCCT), 2012 IEEE International Conference on

Conference_Location

Ramanathapuram

Print_ISBN

978-1-4673-2045-0

Type

conf

DOI

10.1109/ICACCCT.2012.6320821

Filename

6320821