Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions
S. Cha.
International Journal of Mathematical Models and Methods in Applied Sciences 1 (4): 300--307 (2007)

Distance or similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that are applicable to compare two probability density functions, pdf in short, are reviewed and categorized in both syntactic and semantic relationships. A correlation coefficient and a hierarchical clustering technique are adopted to reveal similarities among numerous distance/similarity measures.

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@article{cha2007comprehensive,
  abstract = {Distance or similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that are applicable to compare two probability density functions, pdf in short, are reviewed and categorized in both syntactic and semantic relationships. A correlation coefficient and a hierarchical clustering technique are adopted to reveal similarities among numerous distance/similarity measures.},
  added-at = {2012-06-07T16:45:15.000+0200},
  author = {Cha, Sung-Hyuk},
  biburl = {https://puma.uni-kassel.de/bibtex/269e7c9ba92a049efa4c70f8f0bfdb4ea/jaeschke},
  interhash = {dfaf5e38d33eaab89f3643b242910c81},
  intrahash = {69e7c9ba92a049efa4c70f8f0bfdb4ea},
  journal = {International Journal of Mathematical Models and Methods in Applied Sciences},
  keywords = {distance information ir measure retrieval similarity},
  number = 4,
  pages = {300--307},
  timestamp = {2012-06-08T15:34:11.000+0200},
  title = {Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions},
  url = {http://www.gly.fsu.edu/~parker/geostats/Cha.pdf},
  volume = 1,
  year = 2007
}

%0 Journal Article
%1 cha2007comprehensive
%A Cha, Sung-Hyuk
%D 2007
%J International Journal of Mathematical Models and Methods in Applied Sciences
%K distance information ir measure retrieval similarity
%N 4
%P 300--307
%T Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions
%U http://www.gly.fsu.edu/~parker/geostats/Cha.pdf
%V 1
%X Distance or similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that are applicable to compare two probability density functions, pdf in short, are reviewed and categorized in both syntactic and semantic relationships. A correlation coefficient and a hierarchical clustering technique are adopted to reveal similarities among numerous distance/similarity measures.

PUMA

Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions
S. Cha.
International Journal of Mathematical Models and Methods in Applied Sciences 1 (4): 300--307 (2007)

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PUMA

Comprehensive Survey on Distance/Similarity Measures between Probability Density FunctionsS. Cha. International Journal of Mathematical Models and Methods in Applied Sciences 1 (4): 300--307 (2007)

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Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions
S. Cha.
International Journal of Mathematical Models and Methods in Applied Sciences 1 (4): 300--307 (2007)