I've been working on a handful of projects lately, and had started to keep track which packages contained the algorithms that I use regularly. Some of them are easy to remember, others aren't. My list has been growing, so I'm posting here to make it easy to keep track of. This is a simple table, but shows the name of the algorithm, tasks it can be used for, and the package that contains it.
I'm including algorithms that I have used or intend to use, so this isn't exhaustive. Let me know if there are any glaring omissions.
|Decision Trees||Classification, Regression||rpart|
|Gradient Boosted Machine||Classification, Regression||gbm|
|Linear Regression||Classification, Regression||Base|
|Naïve Bayes||Classification||e1071 or klaR|
|Neural Networks||Classification, Regression||nnet|
|Random Forest||Classification, Regression||randomForest|
|Ridge Regression||Classification, Regression||MASS or ridge|
|Support Vector Machine||Classification, Regression||e1071 or kernlab|
|Linear Discriminant Analysis||Classification||MASS|