Feature selection using expected attainable discrimination
Data(s) |
1998
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Resumo |
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. |
Identificador | |
Publicador |
Elsevier |
Relação |
DOI:10.1016/S0167-8655(98)00014-2 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. |
Direitos |
Elsevier |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #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 |
Tipo |
Journal Article |