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Table 2 Classifier accuracy without filtering

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

ClassifierGermanBanknote authn.HabermanIonosphereSeismic bumpsWDBC
DT0.6920.9810.6860.8790.8980.919
LR0.760.990.7420.8680.9310.954
NB0.7240.8410.7470.8210.8550.934
SVM0.7610.9990.7160.9370.9330.974
NN0.7410.9780.7310.8710.9330.955
RF0.7620.9930.6860.9320.910.961
DES-LA0.7420.9970.7370.9340.9270.964