The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Feature Selection of Interval Valued Data Through Interval K-Means Clustering
|
|
Author(s): D. S. Guru (Department of Studies in Computer Science, University of Mysore, Mysore, India), N. Vinay Kumar (Department of Studies in Computer Science, University of Mysore, Mysore, India)and Mahamad Suhil (Department of Studies in Computer Science, University of Mysore, Mysore, India)
Copyright: 2017
Volume: 7
Issue: 2
Pages: 17
Source title:
International Journal of Computer Vision and Image Processing (IJCVIP)
DOI: 10.4018/IJCVIP.2017040105
Purchase
|
Abstract
This paper introduces a novel feature selection model for supervised interval valued data based on interval K-Means clustering. The proposed model explores two kinds of feature selection through feature clustering viz., class independent feature selection and class dependent feature selection. The former one clusters the features spread across all the samples belonging to all the classes, whereas the latter one clusters the features spread across only the samples belonging to the respective classes. Both feature selection models are demonstrated to explore the generosity of clustering in selecting the interval valued features. For clustering, the kernel of the K-means clustering has been altered to operate on interval valued data. For experimentation purpose four standard benchmarking datasets and three symbolic classifiers have been used. To corroborate the effectiveness of the proposed model, a comparative analysis against the state-of-the-art models is given and results show the superiority of the proposed model.
Related Content
|
Belinda Emmily Tepper, Benjamin Francis, Lijing Wang, Bin Lee.
© 2023.
26 pages.
|
|
Prashant Modi, Sanjay Patel.
© 2022.
19 pages.
|
|
Praveen Kulkarni, Rajesh T. M..
© 2022.
21 pages.
|
|
Jayati Krishna Goswami, Sunita Jalal, Chetan Singh Negi, Anand Singh Jalal.
© 2022.
15 pages.
|
|
Sulochana Nadgeri, Arun Kumar.
© 2022.
18 pages.
|
|
Khalfalla Awedat, Almabrok Essa.
© 2022.
16 pages.
|
|
Abdulhadi Mohammad din Dawrayn, Muhammad Bilal.
© 2022.
16 pages.
|
|
|