UNCERTAINTY AND A NEW MEASURE FOR CLASSIFICATION UNCERTAINTY

Date

2012-08-29

Author

Damgacioglu, Haluk
İyigün, Cem

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Ben-Israel and Iyigun ([1] and [2]) presents a new clustering method which is probabilistic distance clustering (P-D Clustering). In this method, the probability of assignment to cluster for each point is inversely proportional to distances between data point and centers of clusters according to given number of clusters and their centers. In this paper, we study on new uncertainty measure for classification using the assignment probabilities of P-D Clustering. Moreover, the relationship of the new measure with Kullback - Liebner divergence is discussed.

URI

https://hdl.handle.net/11511/52979

Conference Name

10th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS)

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Department of Industrial Engineering, Conference / Seminar

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Citation Formats

H. Damgacioglu and C. İyigün, “UNCERTAINTY AND A NEW MEASURE FOR CLASSIFICATION UNCERTAINTY,” Istanbul, TURKEY, 2012, vol. 7, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52979.