"Feature filtering methods for logistic regression"

The data features are as follows

Stability selection using logistic regression

ImportPandas as PDImportNumPy as NPImportPyechartsImportxlrd#with open (R ' f:\ data analysis dedicated \ Data analysis and machine learning \bankloan.xls ', ' RB ') as F:File = R'f:\ data analysis dedicated \ Data analysis and machine learning \bankloan.xls'Data=pd.read_excel (file)#print (Data.head ())x = data.iloc[:,: 8].values#print (x)y = data.iloc[:, 8].values#print (y) fromSklearn.linear_modelImportLogisticregression as LR fromSklearn.linear_modelImportRandomizedlogisticregression as Rlrrlr=RLR () rlr.fit (x, y) rlr.get_support () validate_feature= data.iloc[:,: 8]Print(U'valid feature is:%s'%','. Join (Validate_feature.columns[rlr.get_support () )) x=data[validate_feature.columns[rlr.get_support ()]].VALUESLR=LR () lr.fit (x, y)Print(U'average correct rate of the model:%s'% Lr.score (x, y))

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"Feature filtering methods for logistic regression"