A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis
Joint Authors
Bennet, Jaison
Arul Ganaprakasam, Chilambuchelvan
Kannan, A.
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days.
The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification.
In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM).
Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used.
The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes.
Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers.
This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community.
This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.
American Psychological Association (APA)
Bennet, Jaison& Arul Ganaprakasam, Chilambuchelvan& Kannan, A.. 2014. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1048691
Modern Language Association (MLA)
Bennet, Jaison…[et al.]. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1048691
American Medical Association (AMA)
Bennet, Jaison& Arul Ganaprakasam, Chilambuchelvan& Kannan, A.. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1048691
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048691