Presenter : YAN-SHOU SIE Authors : Pasi Fränti, Mohammad Rezaei, Qinpei Zhao 2014 . PR

Intelligent Database Systems Lab

Presenter : YAN-SHOU SIE

Authors : PASI FRÄNTI, MOHAMMAD REZAEI, QINPEI ZHAO

2014. PR

Centroid index: Cluster level similarity measure


Outlines

MotivationObjectivesMethodologyExperimentsConclusionsComments


Motivation• Despite this, all external cluster validity indexes

calculate only point-level differences of two partitions without any direct information about how similar their cluster-level structures are.


Objectives

• We propose a cluster level measure to estimate the similarity of two clustering solutions.


• Cluster level similarity

• Duality of centroids and partition

• Centroid index

Methodology


•

Methodology


Methodology


Point-level differences

Methodology


Experiments


Conclusions

• We have introduced a cluster level similarity measure called centroid index (CI), which has clear intuitive interpretation by corresponding to the number of differently allocated clusters.


Comments• Advantages

-Can do Cluster-level measure.• Applications

- Similarity measure.

Presenter : YAN-SHOU SIE Authors : Pasi Fränti, Mohammad Rezaei, Qinpei Zhao 2014 . PR

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