@article{
author = {Gangli Liu; },
title = {A New Index for Clustering Evaluation Based on Density Estimation},
keywords = {Clustering Evaluation; Calinski-Harabasz Index; Silhouette Coefficient; Davies-Bouldin Index; Kernel Density Estimation},
abstract = {A new index for internal evaluation of clustering is introduced. The index is defined as a mixture of two sub-indices. The first sub-index $ I_a $ is called the Ambiguous Index; the second sub-index $ I_s $ is called the Similarity Index. Calculation of the two sub-indices is based on density estimation to each cluster of a partition of the data. An experiment is conducted to test the performance of the new index, and compared with six other internal clustering evaluation indices -- Calinski-Harabasz index, Silhouette coefficient, Davies-Bouldin index, CDbw, DBCV, and VIASCKDE, on a set of 145 datasets. The result shows the new index significantly improves other internal clustering evaluation indices.},
doi = {10.12074/202406.00272V1},
url = {https://chinaxiv.org/abs/202406.00272},
timestamp = {2024-08-12},
}