%0 Journal Article %1 Chen09 %A Chen, Yihua %A Garcia, Eric K. %A Gupta, Maya R. %A Rahimi, Ali %A Cazzanti, Luca %D 2009 %E of Machine Learning Research, The Journal %J The Journal of Machine Learning Research %K learning similarity %P 747--776 %T Similarity-based Classification: Concepts and Algorithms %U http://portal.acm.org/citation.cfm?id=1577069.1577096 %V 10 %X This paper reviews and extends the field of similarity-based classification, presenting new analyses, algorithms, data sets, and a comprehensive set of experimental results for a rich collection of classification problems. Specifically, the generalizability of using similarities as features is analyzed, design goals and methods for weighting nearest-neighbors for similarity-based learning are proposed, and different methods for consistently converting similarities into kernels are compared. Experiments on eight real data sets compare eight approaches and their variants to similarity-based learning.

@article{Chen09, abstract = {This paper reviews and extends the field of similarity-based classification, presenting new analyses, algorithms, data sets, and a comprehensive set of experimental results for a rich collection of classification problems. Specifically, the generalizability of using similarities as features is analyzed, design goals and methods for weighting nearest-neighbors for similarity-based learning are proposed, and different methods for consistently converting similarities into kernels are compared. Experiments on eight real data sets compare eight approaches and their variants to similarity-based learning.}, added-at = {2011-03-24T13:00:26.000+0100}, author = {Chen, Yihua and Garcia, Eric K. and Gupta, Maya R. and Rahimi, Ali and Cazzanti, Luca}, biburl = {https://www.bibsonomy.org/bibtex/27b43211a86f93716435fb4b001378a19/punko}, editor = {of Machine Learning Research, The Journal}, interhash = {1b7eca10d75395a2b3a5f592ff1af511}, intrahash = {7b43211a86f93716435fb4b001378a19}, journal = {The Journal of Machine Learning Research}, keywords = {learning similarity}, month = {June}, pages = {747--776}, timestamp = {2011-03-24T13:00:26.000+0100}, title = {Similarity-based Classification: Concepts and Algorithms}, url = {http://portal.acm.org/citation.cfm?id=1577069.1577096}, volume = 10, year = 2009 }