Table 6. mycoSORT Results - Set of Features F1+F4.

Under-sampling(USF)	Classifier	Precision	Recall	F-measure	MCC	F-2
Training set with USF 0%	Naive Bayes	0.285	0.380	0.326	0.242	0.360
Training set with USF 0%	LMT	0.516	0.107	0.177	0.202	0.130
Training set with USF 0%	LibSVM	1.000	0.020	0.039	0.134	0.020
Training set with USF 5%	Naive Bayes	0.273	0.373	0.315	0.230	0.350
Training set with USF 5%	LMT	0.426	0.173	0.246	0.224	0.200
Training set with USF 5%	LibSVM	0.833	0.033	0.064	0.155	0.040
Training set with USF 10%	Naive Bayes	0.268	0.427	0.329	0.243	0.380
Training set with USF 10%	LMT	0.412	0.233	0.298	0.255	0.260
Training set with USF 10%	LibSVM	0.688	0.073	0.133	0.203	0.090
Training set with USF 15%	Naive Bayes	0.268	0.427	0.329	0.243	0.380
Training set with USF 15%	LMT	0.398	0.300	0.342	0.284	0.320
Training set with USF 15%	LibSVM	0.604	0.193	0.293	0.306	0.220
Training set with USF 20%	Naive Bayes	0.275	0.440	0.338	0.255	0.390
Training set with USF 20%	LMT	0.322	0.393	0.354	0.276	0.380
Training set with USF 20%	LibSVM	0.471	0.327	0.386	0.338	0.350
Training set with USF 25%	Naive Bayes	0.258	0.507	0.342	0.260	0.420
Training set with USF 25%	LMT	0.321	0.520	0.397	0.324	0.460
Training set with USF 25%	LibSVM	0.364	0.420	0.390	0.318	0.410
Training set with USF 30%	Naive Bayes	0.237	0.540	0.329	0.248	0.430
Training set with USF 30%	LMT	0.328	0.500	0.396	0.322	0.450
Training set with USF 30%	LibSVM	0.323	0.473	0.384	0.308	0.430
Training set with USF 35%	Naive Bayes	0.227	0.513	0.315	0.229	0.410
Training set with USF 35%	LMT	0.267	0.587	0.367	0.295	0.470
Training set with USF 35%	LibSVM	0.251	0.573	0.349	0.274	0.460
Training set with USF 40%	Naive Bayes	0.244	0.520	0.332	0.250	0.420
Training set with USF 40%	LMT	0.267	0.707	0.388	0.334	0.530
Training set with USF 40%	LibSVM	0.217	0.613	0.321	0.245	0.450

Results of Positive Class on Feature Setting #2, Using Bio-entities and EC Numbers as Features.