Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

Table 1

Comparison of basic, resampling, and ADABOOST versions of SVM and MLP.

Dataset	MLP	SVM	RMLP	RSVM	ADA-MLP	ADA-SVM
Cleveland	79.2079	82.8383	93.72	85.0886	76.23	82.5083
Statlog	77.4074	84.07	86.6667	83.7037	77.777	84.07
Spect	79.4	81.65	88.38	88.764	79.4007	80.8989
Spectf	76.03	79.40	90.2622	82.397	76.03	77.9026
Eric	77.99	78.95	88.51	83.73	77.9904	77.9904
WBC	95.28	96.85	97.1388	96.5665	95.5651	96.7096
Hepatitis	81.94	85.16	90.3226	85.8065	78.7097	78.9097
Thyroid	96.28	89.77	98.1395	78.6047	97.2093	85.1163
Parkinson	91.28	86.15	96.4103	90.2564	92.3077	87.6923
Pima Indian diabetics	75.13	77.47	79.2969	76.0417	73.9583	77.3438
BUPA liver	71.59	70.14	68.1159	54.4928	71.3043	62.029

R: filter-based supervised instance resampling; ADA: ADABOOST.