2011-06-22T02:21:21-07:00
Resource:Gist
Curated
http://bioinformatics.ubc.ca/gist/
Gist contains software tools for support vector machine classification and for kernel principal components analysis. The SVM portion of Gist is available via an interactive web server. The Gist package contains the following programs:
* gist-train-svm trains a support vector machine based upon a given set of labeled training examples, permitting feature selection and leave-one-out cross-validation,
* gist-classify applies a trained support vector machine to unlabeled data to produce predicted binary classifications.
* gist-fast-classify does the same thing as gist-classify, but uses less time and memory. However, this program only works in conjunction with a linear kernel function.
* gist-kpca performs kernel principal components analysis on a given data set, and
* gist-project projects a data set onto the components discovered by gist-kpca.
In addition to the primary programs, the following auxiliary programs are included:
* gist-fselect performs linear feature selection on a given data set, using binary classification labels,
* gist-matrix performs basic manipulations of matrices,
* gist-score-svm computes performance statistics from the outputs of gist-train-svm and gist-classify,
* gist-rfe performs SVM recursive feature elimination on a given data set,
* gist-sigmoid converts the discriminant values produced by gist-train-svm into probabilities,
* gist2html converts an output file from one of the Gist programs into HTML format, and
* gist-kernel computes a square kernel matrix from a given data file, using a user-specified list of kernel transformations.
Gist is written in ANSI C. Source code, as well as some pre-compiled versions for popular platforms (Linux, Cygwin) can be downloaded.
nlx_68451
Resource:Gist
2011-05-18T00:00:00
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University of British Columbia; British Columbia; Canada
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