The authors come up with a definition of measuring differentiations between features

and then put forward a method of clustering-based feature selection(Below referred to as CBFS).The time complexity of the method is nearly linear with both the size of dataset and the number of features.Besides

the method is applicable to the selection of features in large dataset.It can particularly handle data with both Nominal and Continuous Features.The results of the experiment on UCI datasets show that the method is effective and practicable.