Mathematical Problems in Engineering / 2016 / Article / Tab 6

Research Article

An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem

Table 6

Classification evaluation results for the KNN and C4.5 algorithm with feature selection (NON, CFS, CASH).

AlgorithmF-measure
Feature selectionClassifierNormalDOSPROBER2LU2R

KNN0.9960.9980.9900.9360.876
CFSKNN0.9970.9980.9900.9380.899
CASHKNN0.9990.9980.9900.9360.866
CSFSGKNN0.9970.9970.9890.9420.916
C4.50.9970.9980.9880.9630.966
CFSC4.50.9970.9980.9880.9670.966
CASHC4.50.9970.9890.9690.9420.963
CSFSGC4.50.9970.9980.9530.9680.966

AlgorithmRecall
Feature selectionClassifierNormalDOSPROBER2LU2R

KNN0.9960.9980.9860.7790.6
CFSKNN0.9970.9980.780.7240.8
CASHKNN0.9990.9980.9710.750.4
CSFSGKNN0.9970.9980.9640.7940.6
C4.50.9970.9980.9710.7350.4
CFSC4.50.9970.9980.7880.750.2
CASHC4.50.9970.9890.9670.750.4
CSFSGC4.50.9970.9980.9690.7380.6

AlgorithmROC area
Feature selectionClassifierNormalDOSPROBER2LU2R

KNN0.9960.9980.9900.9830.899
CFSKNN0.9990.9980.9960.9770.99
CASHKNN0.9990.9980.9880.9380.899
CSFSGKNN0.9980.9990.9930.9470.988
C4.50.9990.9980.9920.9370.579
CFSC4.50.9970.9980.9630.8860.733
CASHC4.50.9970.9890.9980.8870.721
CSFSGC4.50.9970.9980.9960.9350.733

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.