Journal of Big Data

Table 2 Classifier accuracy without filtering

From: Improving binary classification using filtering based on k-NN proximity graphs

Classifier	German	Banknote authn.	Haberman	Ionosphere	Seismic bumps	WDBC
DT	0.692	0.981	0.686	0.879	0.898	0.919
LR	0.76	0.99	0.742	0.868	0.931	0.954
NB	0.724	0.841	0.747	0.821	0.855	0.934
SVM	0.761	0.999	0.716	0.937	0.933	0.974
NN	0.741	0.978	0.731	0.871	0.933	0.955
RF	0.762	0.993	0.686	0.932	0.91	0.961
DES-LA	0.742	0.997	0.737	0.934	0.927	0.964

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