Round Randomized Learning Vector Quantization for Brain Tumor Imaging

Table 4

Average accuracy rates with and without multirandomization for all LVQ sibling and MLP, RBF, SOM, and RF classifiers.

Classifier	LVQs		MLP		RBF		SOM		RF
Datasets	Ave BR	Ave AR	BR	AR	BR	AR	BR	AR	BR	AR
Brain images data (PPUKM)	79.28	85.20	56.58	67.76	59.21	71.05	70.39	75	74.34	80.92
Segmented challenge (UCI)	88.45	92.72	88.67	81.33	88.67	90.89	75.78	82.67	92	95.78
Segment test (UCI)	88.27	92.39	67.49	78.19	85.19	88.07	72.02	82.3	88.48	92.18
Image segmentation (UCI)	90.33	93.15	77.2	85.71	85.14	90.48	77.34	80.66	91.92	94.66
Average and STD	86.58 ± 4.96	90.87 ± 3.79	72.49 ± 13.69	78.25 ± 7.64	79.55 ± 13.67	85.12 ± 9.46	73.88 ± 3.23	80.16 ± 3.55	86.69 ± 8.39	90.89 ± 6.81

(i) BR means before multirandomizing data sets.
(ii) AR means after multirandomizing data sets.