Feature selection using expected attainable discrimination
Lovell, D. R., Dance, C. R., Niranjan, M., Prager, R. W., Dalton, K. J., & Derom, R. (1998) Feature selection using expected attainable discrimination. Pattern Recognition Letters, 19(5-6), pp. 393-402.
We propose expected attainable discrimination (EAD) as a measure to select discrete valued features for reliable discrimination between two classes of data. EAD is an average of the area under the ROC curves obtained when a simple histogram probability density model is trained and tested on many random partitions of a data set. EAD can be incorporated into various stepwise search methods to determine promising subsets of features, particularly when misclassification costs are difficult or impossible to specify. Experimental application to the problem of risk prediction in pregnancy is described.
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:||Journal Article|
|Keywords:||Area under the ROC curve, Failure to progress, Feature selection, Receiver operating characteristic (ROC), Risk prediction in pregnancy, Mathematical models, Probability, Random processes, Set theory, Expected attainable discrimination (EAD), Receiver operating characteristics (ROC), Stepwise search methods, Feature extraction|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||07 Jan 2015 05:36|
|Last Modified:||07 Jan 2015 05:36|
Repository Staff Only: item control page