6533b825fe1ef96bd128314a
RESEARCH PRODUCT
Feature selection using ROC curves on classification problems
Juan F. GomezJosé D. MartínR. MagdalenaAntonio J. SerranoEmilio Soriasubject
Receiver operating characteristicbusiness.industryFeature extractionKey (cryptography)Feature selectionLinear classifierPattern recognitionArtificial intelligencebusinessMeasure (mathematics)Power (physics)Mathematicsdescription
Feature Selection (FS) is one of the key stages in classification problems. This paper proposes the use of the area under Receiver Operator Characteristic curves to measure the individual importance of every input as well as a method to discover the variables that yield a statistically significant improvement in the discrimination power of the classification model.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-07-01 | The 2010 International Joint Conference on Neural Networks (IJCNN) |