Skip to Main content Skip to Navigation
Conference papers

A New Criterion for Clusters Validation

Abstract : In this paper a new criterion for clusters validation is proposed. This new cluster validation criterion is used to approximate the goodness of a cluster. The clusters which satisfy a threshold of this measure are selected to participate in clustering ensemble. For combining the chosen clusters, a co-association based consensus function is applied. Since the Evidence Accumulation Clustering method cannot derive the co-association matrix from a subset of clusters, a new EAC based method which is called Extended EAC, EEAC, is applied for constructing the co-association matrix from the subset of clusters. Employing this new cluster validation criterion, the obtained ensemble is evaluated on some well-known and standard data sets. The empirical studies show promising results for the ensemble obtained using the proposed criterion comparing with the ensemble obtained using the standard clusters validation criterion.
Complete list of metadatas

Cited literature [12 references]  Display  Hide  Download

https://hal.inria.fr/hal-01571447
Contributor : Hal Ifip <>
Submitted on : Wednesday, August 2, 2017 - 4:21:57 PM
Last modification on : Thursday, March 5, 2020 - 5:41:56 PM

File

978-3-642-23960-1_14_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Hosein Alizadeh, Behrouz Minaei, Hamid Parvin. A New Criterion for Clusters Validation. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.110-115, ⟨10.1007/978-3-642-23960-1_14⟩. ⟨hal-01571447⟩

Share

Metrics

Record views

224

Files downloads

149