Using upper bounds on attainable discrimination to select discrete valued features
Lovell, D. R., Dance, C. R., Niranjan, M., Prager, R. W., & Dalton, K. J. (1996) Using upper bounds on attainable discrimination to select discrete valued features. In Neural Networks for Signal Processing  VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop, IEEE, Kyoto, pp. 233-242.
Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Conference Paper|
|Keywords:||Algorithms, Calculations, Data reduction, Errors, Estimation, Pattern recognition, Testing, Discrete valued features, Discrimination bound method, Feature selection process, Neural networks|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||07 Jan 2015 05:31|
|Last Modified:||07 Jan 2015 05:31|
Repository Staff Only: item control page