Table 13.

Dataset D on IBD: classification performance of Ph-CNN compared to other classifiers on Healthy vs. iCDf classification task

iCDf	Ph-CNN			LSVM
p	MCC	min CI	max CI	MCC	min CI	max CI
62	0.704	0.655	0.753	0.534	0.484	0.583
124	0.702	0.642	0.760	0.414	0.346	0.482
186	0.680	0.614	0.738	0.662	0.605	0.718
247	0.681	0.614	0.739	0.561	0.507	0.621
	MLPNN			RF
p	MCC	min CI	max CI	MCC	min CI	max CI
62	0.679	0.622	0.739	0.787	0.746	0.831
124	0.690	0.634	0.743	0.811	0.766	0.854
186	0.685	0.630	0.742	0.791	0.741	0.836
247	0.708	0.652	0.764	0.775	0.730	0.820

The performance measure is MCC, with 95% studentized bootstrap confidence intervals (min CI, max CI). Models are computed for p={25%,50%,75% and 100%} of total number of features for each task. Comparing algorithms are linear Support Vector Machines (LSVM), Random Forest (RF) and MultiLayer Perceptron (MLPNN)