There are a variety of different models that perform supervised learning or classification problems
- Diagonal Linear Discriminant Analysis (DLDA)
- Neural Networks (NN)
- Support Vector Machines (SVM)
- k Nearest Neighbors (kNN)
- Bagging
- Boosting
R has a library, MLInterfaces, that puts a uniform interface in front of the input and output from all of these procedures. I could not load the MLInterfaces library directly, but could download and then install the package from
- http://www.bioconductor.org/packages/bioc/1.6/src/contrib/html/MLInterfaces.html
By the way, I am working with a wonderful book now,
- Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Gentleman R, Huber W, Carey VJ, Irizarry RA, Dudoit S (2005) New York, New York: Springer. ISBN: 0387251464. [BookFinder4U link]
that offers a lot of valuable advice on how to use the many advanced features in R and Bioconductor.