A Clustering Performance Measure Based on Fuzzy Set Decomposition

@article{Backer1981ACP,
  title={A Clustering Performance Measure Based on Fuzzy Set Decomposition},
  author={Eric Backer and Anil K. Jain},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={1981},
  volume={PAMI-3},
  pages={66-75}
}
Clustering is primarily used to uncover the true underlying structure of a given data set and, for this purpose, it is desirable to subject the same data to several different clustering algorithms. This paper attempts to put an order on the various partitions of a data set obtained from different clustering algorithms. The goodness of each partition is expressed by means of a performance measure based on a fuzzy set decomposition of the data set under consideration. Several experiments reported… CONTINUE READING
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The inequality in Theorem 1 follows from 7?(x) (1 -71(x)) = 0162-8828

  • The inequality in Theorem 1 follows from 7?(x) (1…
  • 1981

Validity studies in clustering methodologies

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Cluster Analysis by Optimal Decomposition ofInduced Fuzzy Sets

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2 Excerpts

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1 Excerpt

Eric Backer (M'79) was born in Soestdijk, The Netherlands

  • He received the M.S. and Ph.D. degrees in…
  • 1940

2R*(1 -R*) where R* is the Bayes probability of error and n(x) = P {O = II X = x}

  • 2R*(1 -R*) where R* is the Bayes probability of…

I. Introduction

  • I. INTRODUCTION

We give two proofs, one due to Stone and a short original one, of the same result for all distributions of

  • We give two proofs, one due to Stone and a short…

X) (1 -r7(X))} 2R *(1 -R*)

  • E l
  • X) (1 -r7(X))} 2R *(1 -R*)

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