The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Combinatorial Fusion Analysis: Methods and Practices of Combining Multiple Scoring Systems
|
|
Author(s): D. Frank Hsu (Fordham University, USA), Yun-Sheng Chung (National Tsing Hua University, Taiwan)and Bruce S. Kristal (Burke Medical Research Institute and weill Medical College of Cornell University, USA)
Copyright: 2006
Pages: 31
Source title:
Advanced Data Mining Technologies in Bioinformatics
Source Author(s)/Editor(s): Hui-Huang Hsu (Tamkang University, Taipei, Taiwan)
DOI: 10.4018/978-1-59140-863-5.ch003
Purchase
|
Abstract
Combination methods have been investigated as a possible means to improve performance in multi-variable (multi-criterion or multi-objective) classification, prediction, learning, and optimization problems. In addition, information collected from multi-sensor or multi-source environment also often needs to be combined to produce more accurate information, to derive better estimation, or to make more knowledgeable decisions. In this chapter, we present a method, called Combinatorial Fusion Analysis (CFA), for analyzing combination and fusion of multiple scoring. CFA characterizes each Scoring system as having included a Score function, a Rank function, and a Rank/score function. Both rank combination and score combination are explored as to their combinatorial complexity and computational efficiency. Information derived from the scoring characteristics of each scoring system is used to perform system selection and to decide method combination. In particular, the rank/score graph defined by Hsu, Shapiro and Taksa (Hsu et al., 2002; Hsu & Taksa, 2005) is used to measure the diversity between scoring systems. We illustrate various applications of the framework using examples in information retrieval and biomedical informatics.
Related Content
|
Linkon Chowdhury, Md Sarwar Kamal, Shamim H. Ripon, Sazia Parvin, Omar Khadeer Hussain, Amira Ashour, Bristy Roy Chowdhury.
© 2024.
20 pages.
|
|
Mousomi Roy.
© 2024.
21 pages.
|
|
Nassima Dif, Zakaria Elberrichi.
© 2024.
20 pages.
|
|
Pyingkodi Maran, Shanthi S., Thenmozhi K., Hemalatha D., Nanthini K..
© 2024.
16 pages.
|
|
Mohamed Nadjib Boufenara, Mahmoud Boufaida, Mohamed Lamine Berkane.
© 2024.
16 pages.
|
|
Meroua Daoudi, Souham Meshoul, Samia Boucherkha.
© 2024.
25 pages.
|
|
Zhongyu Lu, Qiang Xu, Murad Al-Rajab, Lamogha Chiazor.
© 2024.
56 pages.
|
|
|