Title: A Comparative Study of Different Distances for Similarity Estimation
Abstract: Distance metric is widely used in similarity estimation. The smaller the distance is, the greater the similarity is. The Minkowski distance metric are usually chosen as the similarity measure in the conventional similarity metrics. In this paper, the most popular Euclidean and Manhattan distance, and the morphology similarity distance we have proposed are compared as similarity estimation measure distance. We cluster thirty random datasets using the fuzzy c-mean algorithm, recognize the Iris data from the UCI repository, and the experiment results are compared and analyzed.
Publication Year: 2011
Publication Date: 2011-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
Access and Citation
Cited By Count: 18
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