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Presenter : Kung, Chien-Hao Authors : Eghbal G. Mansoori 2011,IEEE

FRBC: A Fuzzy Rule-Based Clustering Algorithm. Presenter : Kung, Chien-Hao Authors : Eghbal G. Mansoori 2011,IEEE. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation.

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Presenter : Kung, Chien-Hao Authors : Eghbal G. Mansoori 2011,IEEE

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  1. FRBC: A Fuzzy Rule-Based Clustering Algorithm Presenter : Kung, Chien-HaoAuthors : Eghbal G. Mansoori2011,IEEE

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. Motivation • Clustering response is a primitive exploratory approach in data analysis with little or no prior knowledge. • However, the main challenge for most of clustering algorithms is their necessity to know the number of clusters for which to look.

  4. Objectives • To overcome these restrictions, a novel fuzzy rule-based clustering algorithm(FRBC) is proposed in this paper. • FRBC tries to automatically explore the potential clusters in the data patterns.

  5. Methodology-Fuzzy • Fuzzification • Fuzzy Rule • Fuzzy Inference Mechanism • Defuzzifierion

  6. Methodology Generate auxiliary data Choose the best rule Clustering Regroup remained data

  7. Methodology Generate auxiliary data Choose the best rule Clustering Regroup remained data

  8. Methodology Generate auxiliary data Choose the best rule Clustering Regroup remained data

  9. Methodology Generate auxiliary data Choose the best rule Clustering Regroup remained data

  10. Methodology Generate auxiliary data Choose the best rule Clustering Regroup remained data

  11. Experiment

  12. Experiment

  13. Experiment

  14. Experiment T=0.1 T=0.01

  15. Experiment

  16. Experiment

  17. Conclusions • FRBC is a novel fuzzy rule-based clustering algorithm to automatically explore the potential clusters. • The clusters specified by fuzzy rules are human understandable with acceptable accuracy.

  18. Comments • Advantages/drawbacks • This paper gives rich experiments for this method • But this method still has a parameter (threshold) to control the number of clusters. • Applications • Clustering.

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