# Some new indexes of cluster validity

@article{Bezdek1998SomeNI, title={Some new indexes of cluster validity}, author={James C. Bezdek and Nikhil Ranjan Pal}, journal={IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society}, year={1998}, volume={28 3}, pages={ 301-15 } }

We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index). We illustrate two deficiencies of Dunn's index which make it overly sensitive to noisy clusters and propose several generalizations of it that are not as brittle to outliers in the clusters. Our numerical examples show that the standard measure of interset distance (the minimum distance between points in a pair of…

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## 1,102 Citations

Some new indexes of cluster validity

- Mathematics, MedicineIEEE Trans. Syst. Man Cybern. Part B
- 1998

This work reviews two clustering algorithms and three indexes of crisp cluster validity and shows that while Dunn's original index has operational flaws, the concept it embodies provides a rich paradigm for validation of partitions that have cloud-like clusters.

Validity index for crisp and fuzzy clusters

- Mathematics, Computer SciencePattern Recognit.
- 2004

A cluster validity index and its fuzzification is described, which can provide a measure of goodness of clustering on different partitions of a data set, and results demonstrating the superiority of the PBM-index in appropriately determining the number of clusters are provided.

A new validity index for crisp clusters

- Computer Science, MathematicsPattern Analysis and Applications
- 2015

A new cluster validity index, called the STR index, is defined as the product of two components which determine changes of compactness and separability of clusters during a clustering process, and the maximum value identifies the best clustering scheme.

A comprehensive validity index for clustering

- Mathematics, Computer ScienceIntell. Data Anal.
- 2008

A new bounded index for cluster validity called the score function (SF), a double exponential expression that is based on a ratio of standard cluster parameters that is shown to work well on multidimensional and noisy data sets.

A new cluster validity index for prototype based clustering algorithms based on inter- and intra-cluster density

- Mathematics2007 International Joint Conference on Neural Networks
- 2007

One of the fundamental challenges of clustering is how to evaluate, without auxiliary information, to what extent the obtained clusters fit the natural partitions of the data s et. A common approach…

Clustering performance analysis using new correlation based cluster validity indices

- Computer Science, MathematicsArXiv
- 2021

Two new cluster validity indices are developed based on a correlation between an actual distance between a pair of data points and a centroid distance of clusters that the two points locate in which overcome the weakness previously stated.

Some connectivity based cluster validity indices

- Mathematics, Computer ScienceAppl. Soft Comput.
- 2012

It is empirically established that incorporation of the property of connectivity significantly improves the capabilities of these indices in identifying the appropriate number of clusters and also shows that connectivity based Dunn-index performs the best as compared to all the other six indices.

Performance Evaluation of Some Symmetry-Based Cluster Validity Indexes

- Mathematics, Computer ScienceIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
- 2009

It is empirically established that incorporation of the property of symmetry significantly improves the capabilities of these indexes in identifying the appropriate number of clusters.

Mutual equidistant-scattering criterion: A new index for crisp clustering

- Computer ScienceExpert Syst. Appl.
- 2019

This work proposes a new non-parametric internal validity index based on within-cluster mutual equidistant-scattering for crisp clustering and shows the effectiveness and reliability of this approach to evaluate the hyperparameter K.

A Bounded Index for Cluster Validity

- Computer Science, MathematicsMLDM
- 2007

A new bounded index for cluster validity, called the score function (SF), is introduced, based on standard cluster properties, and is shown to work well on multi-dimensional data sets and is able to accommodate unique and sub-cluster cases.

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