Parasites & Vectors

Table 2 Algorithms and parameters considered in the ML/IA analysis

From: Machine learning approach to support taxonomic species discrimination based on helminth collections data

Algorithms	MM + GL + H
Algorithms	Correct instances (%)	Kappa	Specificity	Sensitivity	AUC	Accuracy	NPV	PPV
J48	93.172	0.92	0.962	0.966	0.979	0.964	0.965	0.964
Random Tree	89.257	0.89	0.934	0.951	0.944	0.942	0.949	0.936
REPTree	90.963	0.90	0.959	0.945	0.986	0.952	0.943	0.961
LMT	96.385	0.96	0.981	0.982	0.999	0.981	0.981	0.982
Majority Voting	94.679	0.94	0.974	0.970	0.972	0.964	0.969	0.975

Algorithms	MM + H
Algorithms	Correct instances (%)	Kappa	Specificity	Sensitivity	AUC	Accuracy	NPV	PPV
J48	88.253	0.88	0.932	0.941	0.955	0.937	0.939	0.934
Random Tree	86.646	0.86	0.949	0.935	0.93	0.942	0.933	0.950
REPTree	85.943	0.85	0.919	0.911	0.979	0.915	0.908	0.921
LMT	93.975	0.94	0.965	0.972	0.998	0.968	0.971	0.966
Majority Voting	91.867	0.91	0.955	0.959	0.957	0.957	0.958	0.956

Algorithms	MM + GL
Algorithms	Correct instances (%)	Kappa	Specificity	Sensitivity	AUC	Accuracy	NPV	PPV
J48	92.570	0.92	0.960	0.961	0.975	0.961	0.960	0.961
Random Tree	91.566	0.91	0.951	0.959	0.956	0.955	0.958	0.953
REPTree	89.056	0.88	0.942	0.941	0.98	0.941	0.939	0.944
LMT	96.686	0.96	0.984	0.982	0.999	0.983	0.981	0.985
Majority Voting	95.683	0.95	0.980	0.975	0.978	0.978	0.975	0.980

Algorithms	MM
Algorithms	Correct instances (%)	Kappa	Specificity	Sensitivity	AUC	Accuracy	NPV	PPV
J48	84.538	0.84	0.918	0.912	0.912	0.915	0.909	0.920
Random Tree	82.228	0.81	0.885	0.917	0.917	0.901	0.915	0.888
REPTree	84.337	0.83	0.915	0.912	0.912	0.914	0.909	0.918
LMT	91.867	0.91	0.956	0.958	0.958	0.957	0.957	0.957
Majority Voting	89.056	0.88	0.934	0.949	0.949	0.941	0.947	0.936

Performance of algorithms is reported as specificity, sensitivity and accuracy following [24] and as corrected classified instances, kappa coefficient and AUC, as generated by Weka 3.8.3 software
MM morphological and morphometric data, GL geographical location, H host, AUC area under the receiver-operating characteristic (ROC) curve, NPV negative predictive value, PPV positive predictive value

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ISSN: 1756-3305

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