BMC Bioinformatics

Table 5 Prediction accuracies of five runs of HBSA-KNN-based ensemble classifier on six test sets

From: Finding minimum gene subsets with heuristic breadth-first search algorithm for robust tumor classification

Run	First	Second	Third	Fourth	Fifth	Average
Dataset	Acc.%	Acc.%	Acc.%	Acc.%	Acc.%	Acc.%
Leukemia	86.54	84.62	88.46	84.62	84.62	85.57 ± 1.66
DLBCL	90.48	90.48	90.48	85.71	90.48	89.53 ± 2.13
Prostate	85.29	82.35	85.29	85.29	85.29	84.70 ± 1.31
SRBCT	95	95	95	90	95	94 ± 2.24
ALL	95	97	96	95	95	95.60 ± 0.89
Colon	75	75	75	75	75	75 ± 0

Column First denotes the prediction accuracy of the constructed ensemble classifier obtained on the first run of the HBSA-KNN, and the others are deduced by analogy. The average accuracy is the average prediction accuracy obtained by five runs of the HBSA-KNN.

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ISSN: 1471-2105

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