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

Table 5

Performance comparison for the individual algorithm using the CLD feature sorted by 1.

Type	Algorithm	ACC	SPE	SEN	1	MCC	PPV	AUC
Trees	SimpleCart	0.653	0.651	0.652	0.653	0.303	0.647	0.653
Trees	REPTree	0.650	0.650	0.649	0.650	0.300	0.649	0.650
Trees	FT	0.645	0.649	0.641	0.646	0.288	0.658	0.646
Rules	DecisionTable	0.642	0.650	0.639	0.644	0.288	0.663	0.644
Rules	DTNB	0.642	0.650	0.639	0.644	0.288	0.663	0.644
Trees	NBTree	0.643	0.648	0.639	0.644	0.287	0.661	0.644
Bayes	BayesNet	0.642	0.647	0.640	0.643	0.286	0.657	0.643
Trees	ADTree	0.642	0.644	0.641	0.643	0.283	0.646	0.643
Rules	Ridor	0.614	0.659	0.639	0.642	0.257	0.635	0.647
Trees	LADTree	0.642	0.648	0.641	0.642	0.287	0.653	0.644
Trees	LMT	0.639	0.656	0.625	0.640	0.280	0.693	0.640
Rules	PART	0.639	0.655	0.625	0.639	0.278	0.695	0.639
Trees	J48	0.639	0.655	0.627	0.639	0.280	0.689	0.641
Trees	J48graft	0.639	0.655	0.627	0.639	0.280	0.689	0.641
Rules	Jrip	0.637	0.639	0.638	0.638	0.277	0.634	0.638
Rules	OneR	0.635	0.629	0.641	0.635	0.269	0.610	0.634
Functions	VotedPerceptron	0.611	0.579	0.697	0.632	0.248	0.392	0.638
Lazy	LWL	0.612	0.582	0.683	0.629	0.246	0.431	0.632
Trees	DecisionStump	0.612	0.582	0.684	0.629	0.246	0.428	0.632
Rules	ConjunctiveRule	0.613	0.583	0.681	0.628	0.245	0.437	0.631
Bayes	NaiveBayes	0.619	0.595	0.656	0.623	0.242	0.496	0.627
Bayes	NaiveBayesSimple	0.619	0.595	0.656	0.623	0.242	0.496	0.627
Bayes	NaiveBayesUpdateable	0.619	0.595	0.656	0.623	0.242	0.496	0.627
Trees	RandomForest	0.623	0.616	0.631	0.623	0.247	0.591	0.624
Lazy	Ibk	0.622	0.613	0.632	0.622	0.242	0.586	0.622
Trees	RandomTree	0.622	0.613	0.632	0.622	0.242	0.586	0.622
Bayes	BayesianLogisticRegression	0.621	0.612	0.630	0.621	0.240	0.583	0.621
Functions	Logistic	0.621	0.612	0.631	0.621	0.241	0.582	0.621
Functions	SimpleLogistic	0.621	0.612	0.633	0.621	0.241	0.578	0.621
Functions	SMO	0.619	0.607	0.640	0.621	0.245	0.549	0.622
Lazy	Kstar	0.619	0.606	0.640	0.620	0.242	0.547	0.623
Functions	MultilayerPerceptron	0.618	0.598	0.649	0.620	0.242	0.518	0.621
Functions	RBFNetwork	0.618	0.598	0.647	0.620	0.240	0.517	0.620
Lazy	IB1	0.594	0.564	0.683	0.619	0.214	0.351	0.624
Rules	Nnge	0.544	0.601	0.529	0.562	0.106	0.832	0.564
Misc	HyperPipes	0.510	0.510	0.510	0.510	0.010	0.510	0.510
Rules	ZeroR	0.510	0.510	0.510	0.510	0.010	0.510	0.510
Bayes	NaiveBayesMultinomial	0.500	0.561	0.447	0.480	−0.008	0.489	0.569
Misc	VFI	0.500	NA	0.500	NA	NA	1.000	NA