Transcription of Understanding of Internal Clustering Validation Measures
{{id}} {{{paragraph}}}
Example: bankruptcy
Understanding of Internal Clustering Validation Measures
2010 IEEE International Conference on Data Mining Understanding of Internal Clustering Validation Measures Yanchi Liu1,2 , Zhongmou Li2 , Hui Xiong2 , Xuedong Gao1 , Junjie Wu3. 1. School of Economics and Management, University of Science and Technology Beijing, China 2. MSIS Department, Rutgers Business School, Rutgers University, USA. 3. School of Economics and Management, Beihang University, China Abstract Clustering Validation has long been recognized without any additional information. In practice, external as one of the vital issues essential to the success of clus- information such as class labels is often not available in tering applications.
Unlike external validation measures, which use external information not present in the data, internal validation mea-sures only rely on information in the data. The internal measures evaluate the goodness of a clustering structure without respect to external information [4]. Since external validation measures know the “true” cluster number in
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: