python中不平衡類的處理方法

1.combine中SMOTEENNfrombineimportsmSMOTEENN()X_resampled,y_resampledsm.fit_sample(X,y)2.combine中SMOTETomekfrombineimportsmSMOTETomek()X_resampled,y_resampledsm.fit_sample(X,y)ensembleBalanceCascadefromimblearn.ensembleimportBalanceCascadebcBalanceCascade()X_resampledy_resampled=bc.fit_sample(y)4.

ensemble中

EasyEnsemblefromimblearn.ensembleimportEasyEnsembleeeEasyEnsemble()X_resampledy_resampled=ee.fit_sample(y)5.的ADASYNfromimblearn.over_samplingimportADASYNada=X_resampledy_resampled=ada.fit_sample(,y)6.的RandomOverSamplerfromimblearn.over_samplingimportRandomOverSamplerros=RandomOverSampler()X_resampledy_resampled=ros.fit_sample(,y)7.的SMOTEfromimblearn.over_samplingimportSMOTEsmSMOTE(kind='regular'X_resampledy_resampled=sm.fit_sample(y)8.的SMOTEfromimblearn.over_samplingimportSMOTEsmSMOTE(kind='borderline1')X_resampledy_resampled=sm.fit_sample(y)9.的SMOTEfromimblearn.over_samplingimportSMOTEsm=SMOTE(kind='borderline2')X_resampledy_resampled=sm.fit_sample(y)

10.的SMOTEfromimblearn.over_samplingimportSMOTEsmSMOTE(kind='svm')X_resampledy_resampled=sm.fit_sample(y)11.fromimblearn.under_samplingimportEditedNearestNeighbours,RepeatedEditedNearestNeighbours)enn=EditedNearestNeighbours()X_resampledy_resampled=enn.fit_sample(,y)rennRepeatedEditedNearestNeighbours()X_resampledy_resampled=renn.fit_sample(,y)allknnAllKNN()X_resampledy_resampled=allknn.fit_sample(,y)12.fromimblearn.under_samplingimportClusterCentroidsccClusterCentroids()X_resampledy_resampled=cc.fit_sample(y)13.fromimblearn.under_samplingimportCondensedNearestNeighbourcnn=CondensedNearestNeighbour()X_resampledy_resampled=cnn.fit_sample(,y)14.fromimblearn.under_samplingimportEditedNearestNeighboursenn=EditedNearestNeighbours()X_resampledy_resampled=enn.fit_sample(,y)15.fromimblearn.under_samplingimportnm1=version1X_resampledy_resampled=nm1.fit_sample(,y)16.fromimblearn.under_samplingimportnm1=version2X_resampledy_resampled=nm1.fit_sample(,y)

17.fromimblearn.under_samplingimportnm1=version2X_resampledy_resampled=nm1.fit_sample(,y)18.fromimblearn.under_samplingimportNeighbourhoodCleaningRulencl=NeighbourhoodCleaningRule()X_resampledy_resampled=ncl.fit_sample(,y)19.fromimblearn.under_samplingimportOneSidedSelectionoss=OneSidedSelection()X_resampledy_resampled=oss.fit_sample(,y)20.fromimblearn.under_samplingimportRandomUnderSamplerrus=RandomUnderSampler()X_resampledy_resampled=rus.fit_sample(,y)21fromimblearn.under_samplingimport(EditedNearestNeighbours,RepeatedEditedNearestNeighbours)enn=EditedNearestNeighbours()X_resampledy_resampled=enn.fit_sample(,y)rennRepeatedEditedNearestNeighbours()X_resa