%0 Journal Article %1 914517 %A Muller, K.-R. %A Mika, S. %A Ratsch, G. %A Tsuda, K. %A Scholkopf, B. %D 2001 %J Neural Networks, IEEE Transactions on %K algorithms based introduction kernel learning %N 2 %P 181 -201 %R 10.1109/72.914517 %T An introduction to kernel-based learning algorithms %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=914517&tag=1 %V 12 %X This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis

@article{914517, abstract = {This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis}, added-at = {2012-12-31T23:15:21.000+0100}, author = {Muller, K.-R. and Mika, S. and Ratsch, G. and Tsuda, K. and Scholkopf, B.}, biburl = {https://www.bibsonomy.org/bibtex/2703b5732bd5d7b811b95e38ac884b8df/johncsnyder}, description = {IEEE Xplore - An introduction to kernel-based learning algorithms}, doi = {10.1109/72.914517}, interhash = {979af0f9b1ffbb6e228d19f946f002e1}, intrahash = {703b5732bd5d7b811b95e38ac884b8df}, issn = {1045-9227}, journal = {Neural Networks, IEEE Transactions on}, keywords = {algorithms based introduction kernel learning}, month = mar, number = 2, pages = {181 -201}, timestamp = {2012-12-31T23:15:21.000+0100}, title = {An introduction to kernel-based learning algorithms}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=914517&tag=1}, volume = 12, year = 2001 }