Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms

Table 7

Performance evaluation for OMIM and HLungDB datasets.

Type	Algorithm	Hit number	Hit ratio
Rules	Ridor	1164	0.894
Rules	ZeroR	1159	0.890
Trees	ADTree	1119	0.859
Misc	HyperPipes	1115	0.856
Functions	MultilayerPerceptron	1076	0.826
Trees	LADTree	1061	0.815
Rules	OneR	1047	0.804
Lazy	IB1	1023	0.786
Lazy	IBk	1023	0.786
Bayes	BayesNet	1020	0.783
Rules	PART	1019	0.783
Trees	J48graft	1018	0.782
Trees	J48	1017	0.781
Rules	DecisionTable	1011	0.776
Trees	FT	1004	0.771
Lazy	KStar	999	0.767
Bayes	BayesianLogisticRegression	998	0.767
Trees	NBTree	995	0.764
Rules	DTNB	991	0.761
Trees	RandomTree	988	0.759
Trees	LMT	983	0.755
Trees	REPTree	975	0.749
Trees	SimpleCart	973	0.747
Trees	RandomForest	973	0.747
Rules	JRip	966	0.742
Functions	Logistic	964	0.740
Functions	SimpleLogistic	964	0.740
Functions	SMO	944	0.725
Functions	RBFNetwork	925	0.710
Functions	VotedPerceptron	844	0.648
Bayes	NaiveBayesSimple	827	0.635
Bayes	NaiveBayes	826	0.634
Bayes	NaiveBayesUpdateable	826	0.634
Bayes	NaiveBayesMultinomial	796	0.611
Rules	NNge	94	0.072