Enhanced CABOSFV clustering algorithm based on adaptive threshold

摘要

In the light of the sensitivity of the order of data input by CABOSFV clustering algorithm, to enhance performance of CABOSFV, this paper puts forward a novel algorithm to gain an adaptive its threshold on the line(APCABOSFV). In the end experiments on artificial l data sets show demonstrate that the accuracy of the proposed APCABOSFV algorithm outperforms existing CABOSFV clustering algorithm for clustering high-dimensional sparse data.