Ground truth bias in external cluster validity indices
Yang Lei, James C Bezdek, Simone Romano, Xuan Vinh Nguyen, Jeffrey Chan, James Bailey
Pattern Recognition | ELSEVIER SCI LTD | Published : 2017
External cluster validity indices (CVIs) are used to quantify the quality of a clustering by comparing the similarity between the clustering and a ground truth partition. However, some external CVIs show a biased behavior when selecting the most similar clustering. Users may consequently be misguided by such results. Recognizing and understanding the bias behavior of CVIs is therefore crucial. It has been noticed that, some external CVIs exhibit a preferential bias towards a larger or smaller number of clusters which is monotonic (directly or inversely) in the number of clusters in candidate partitions. This type of bias is caused by the functional form of the CVI model. For example, the pop..View full abstract
This work was supported by the Australian Research Council (ARC) and the China Scholarship Council (CSC).