medSTC-package: Max-margin supervised Sparse Topical Coding model (Med-STC)

Description Details Author(s) References See Also Examples

Description

This package employs sparse topical coding models for multi-class classification developed by Jun Zhu and Eric P. Xing. The package uses a fast C implementation of SVM, SVMlight (http://svmlight.joachims.org/), developed by Thorsten Joachims <[email protected]>.

Details

Package: medSTC
Type: Package
Version: 1.0.0
Date: 2013-1-15
License: GPL
LazyLoad: yes

Author(s)

Jun Zhu ([email protected]), Aykut Firat ([email protected])

References

Jun Zhu, and Eric P. Xing. Sparse Topical Coding, In Proc. of 27th Conference on Uncertainty in Artificial Intelligence (UAI), Barcelona, Spain, 2011. T. Joachims, Making large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning, B. Scholkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999. http://www-ai.cs.uni-dortmund.de/DOKUMENTE/joachims_99a.pdf

See Also

Functions to fit models: medSTC

Functions for prediction: predict.medSTC

Included data sets: newsgroups

Examples

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## See the demo for the newsgroup example:
## Not run: demo(medSTC)

medSTC documentation built on May 29, 2017, 5:13 p.m.