Table 5. mycoSORT Results - Set of Features F1.

Under-sampling(USF)	Classifier	Precision	Recall	F-measure	MCC	F-2
Training set with USF 0%	Naive Bayes	0.286	0.227	0.253	0.182	0.240
Training set with USF 0%	LMT	0.492	0.207	0.291	0.274	0.230
Training set with USF 0%	LibSVM	0.714	0.033	0.064	0.140	0.04
Training set with USF 5%	Naive Bayes	0.294	0.280	0.287	0.210	0.280
Training set with USF 5%	LMT	0.461	0.233	0.310	0.278	0.260
Training set with USF 5%	LibSVM	0.645	0.133	0.221	0.264	0.160
Training set with USF 10%	Naive Bayes	0.269	0.307	0.287	0.202	0.300
Training set with USF 10%	LMT	0.376	0.213	0.272	0.226	0.230
Training set with USF 10%	LibSVM	0.47	0.207	0.287	0.264	0.230
Training set with USF 15%	Naive Bayes	0.301	0.347	0.322	0.241	0.340
Training set with USF 15%	LMT	0.352	0.413	0.380	0.307	0.400
Training set with USF 15%	LibSVM	0.387	0.287	0.330	0.271	0.300
Training set with USF 20%	Naive Bayes	0.263	0.340	0.297	0.209	0.320
Training set with USF 20%	LMT	0.348	0.480	0.403	0.331	0.450
Training set with USF 20%	LibSVM	0.353	0.353	0.353	0.281	0.350
Training set with USF 25%	Naive Bayes	0.243	0.353	0.288	0.197	0.320
Training set with USF 25%	LMT	0.286	0.547	0.375	0.301	0.460
Training set with USF 25%	LibSVM	0.282	0.413	0.335	0.251	0.380
Training set with USF 30%	Naive Bayes	0.277	0.440	0.340	0.257	0.390
Training set with USF 30%	LMT	0.291	0.627	0.397	0.334	0.510
Training set with USF 30%	LibSVM	0.258	0.48	0.336	0.252	0.410
Training set with USF 35%	Naive Bayes	0.242	0.440	0.312	0.223	0.380
Training set with USF 35%	LMT	0.233	0.620	0.338	0.266	0.470
Training set with USF 35%	LibSVM	0.210	0.633	0.316	0.241	0.450
Training set with USF 40%	Naive Bayes	0.254	0.467	0.329	0.243	0.400
Training set with USF 40%	LMT	0.269	0.660	0.382	0.321	0.510
Training set with USF 40%	LibSVM	0.196	0.667	0.303	0.229	0.450

Results of Positive Class on Feature Setting #1, Using Only Bio-entities as Features.