SRBCTSmall Round Blue-Cell Tumor
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The proposed model proved its capability to select features from large datasets, when applied on SRBCT microarray dataset.
[23] Heart Disease - 6.1/88.22% 8.08/ 86.67% On average On average Breast cancer 11/91.23% 13.5/98.12% 5.89/95.99 (Wisconsin On average On average diagnostic) Thyroid - - - Table 9: The selected features subsets using the proposed ACO model that achieved the best accuracy /feature subset for SRBCT. No.
For SRBCT we have used the dataset used by Khan [13].
For SRBCT dataset maximum classification accuracy of 100% is achieved with 15 genes with LDC and SVM classifier using MICE.