Table 10 Open in new tab Voting results... | Oxford Academic

Table 10

Open in new tab

Voting results and single model results of eight models on accuracy, precision, specificity, balanced average (F1-score), consistency test index (kappa) and recall; the top 1 of each indicators were marked as bold text

	Accuracy	Recall	Precision	Specificity	F1-score	Kappa
Vote_1	0.734820	0.927357	0.690474	0.334298	0.768811	0.257488
Vote_2	0.756605	0.863349	0.705754	0.457933	0.753761	0.327965
Vote_3	0.768086	0.824571	0.721773	0.532612	0.746595	0.363039
Vote_4	0.785580	0.794663	0.720453	0.606143	0.731923	0.395788
Vote_5	0.784754	0.752909	0.722685	0.683765	0.712288	0.425853
Vote_6	0.786689	0.706961	0.727658	0.760024	0.691929	0.451502
Vote_7	0.777391	0.640642	0.730498	0.837807	0.657155	0.442357
Vote_8	0.727814	0.518230	0.707729	0.923482	0.570414	0.374407
FNN	0.798308	0.791062	0.767744	0.725392	0.760613	0.491853
KNN	0.729326	0.688061	0.700937	0.657092	0.659602	0.320299
XGBoost	0.786030	0.803387	0.737362	0.615127	0.744092	0.419844
NB	0.720282	0.662418	0.690309	0.643922	0.643178	0.280391
RF	0.762731	0.760221	0.690735	0.598778	0.697785	0.353804
SVM	0.765061	0.778616	0.718526	0.581766	0.720179	0.359531
GC	0.792923	0.776271	0.728246	0.693327	0.733131	0.445779
LSTM	0.767079	0.768647	0.726224	0.620660	0.722073	0.386801

	Accuracy	Recall	Precision	Specificity	F1-score	Kappa
Vote_1	0.734820	0.927357	0.690474	0.334298	0.768811	0.257488
Vote_2	0.756605	0.863349	0.705754	0.457933	0.753761	0.327965
Vote_3	0.768086	0.824571	0.721773	0.532612	0.746595	0.363039
Vote_4	0.785580	0.794663	0.720453	0.606143	0.731923	0.395788
Vote_5	0.784754	0.752909	0.722685	0.683765	0.712288	0.425853
Vote_6	0.786689	0.706961	0.727658	0.760024	0.691929	0.451502
Vote_7	0.777391	0.640642	0.730498	0.837807	0.657155	0.442357
Vote_8	0.727814	0.518230	0.707729	0.923482	0.570414	0.374407
FNN	0.798308	0.791062	0.767744	0.725392	0.760613	0.491853
KNN	0.729326	0.688061	0.700937	0.657092	0.659602	0.320299
XGBoost	0.786030	0.803387	0.737362	0.615127	0.744092	0.419844
NB	0.720282	0.662418	0.690309	0.643922	0.643178	0.280391
RF	0.762731	0.760221	0.690735	0.598778	0.697785	0.353804
SVM	0.765061	0.778616	0.718526	0.581766	0.720179	0.359531
GC	0.792923	0.776271	0.728246	0.693327	0.733131	0.445779
LSTM	0.767079	0.768647	0.726224	0.620660	0.722073	0.386801

Table 10

Open in new tab

Voting results and single model results of eight models on accuracy, precision, specificity, balanced average (F1-score), consistency test index (kappa) and recall; the top 1 of each indicators were marked as bold text

	Accuracy	Recall	Precision	Specificity	F1-score	Kappa
Vote_1	0.734820	0.927357	0.690474	0.334298	0.768811	0.257488
Vote_2	0.756605	0.863349	0.705754	0.457933	0.753761	0.327965
Vote_3	0.768086	0.824571	0.721773	0.532612	0.746595	0.363039
Vote_4	0.785580	0.794663	0.720453	0.606143	0.731923	0.395788
Vote_5	0.784754	0.752909	0.722685	0.683765	0.712288	0.425853
Vote_6	0.786689	0.706961	0.727658	0.760024	0.691929	0.451502
Vote_7	0.777391	0.640642	0.730498	0.837807	0.657155	0.442357
Vote_8	0.727814	0.518230	0.707729	0.923482	0.570414	0.374407
FNN	0.798308	0.791062	0.767744	0.725392	0.760613	0.491853
KNN	0.729326	0.688061	0.700937	0.657092	0.659602	0.320299
XGBoost	0.786030	0.803387	0.737362	0.615127	0.744092	0.419844
NB	0.720282	0.662418	0.690309	0.643922	0.643178	0.280391
RF	0.762731	0.760221	0.690735	0.598778	0.697785	0.353804
SVM	0.765061	0.778616	0.718526	0.581766	0.720179	0.359531
GC	0.792923	0.776271	0.728246	0.693327	0.733131	0.445779
LSTM	0.767079	0.768647	0.726224	0.620660	0.722073	0.386801

	Accuracy	Recall	Precision	Specificity	F1-score	Kappa
Vote_1	0.734820	0.927357	0.690474	0.334298	0.768811	0.257488
Vote_2	0.756605	0.863349	0.705754	0.457933	0.753761	0.327965
Vote_3	0.768086	0.824571	0.721773	0.532612	0.746595	0.363039
Vote_4	0.785580	0.794663	0.720453	0.606143	0.731923	0.395788
Vote_5	0.784754	0.752909	0.722685	0.683765	0.712288	0.425853
Vote_6	0.786689	0.706961	0.727658	0.760024	0.691929	0.451502
Vote_7	0.777391	0.640642	0.730498	0.837807	0.657155	0.442357
Vote_8	0.727814	0.518230	0.707729	0.923482	0.570414	0.374407
FNN	0.798308	0.791062	0.767744	0.725392	0.760613	0.491853
KNN	0.729326	0.688061	0.700937	0.657092	0.659602	0.320299
XGBoost	0.786030	0.803387	0.737362	0.615127	0.744092	0.419844
NB	0.720282	0.662418	0.690309	0.643922	0.643178	0.280391
RF	0.762731	0.760221	0.690735	0.598778	0.697785	0.353804
SVM	0.765061	0.778616	0.718526	0.581766	0.720179	0.359531
GC	0.792923	0.776271	0.728246	0.693327	0.733131	0.445779
LSTM	0.767079	0.768647	0.726224	0.620660	0.722073	0.386801