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Machine Learning Packages in R

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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.

Algorithm Uses Package
Decision Trees Classification, Regression rpart
Gradient Boosted Machine Classification, Regression gbm
Hierarchical Clustering Clustering pvclust
k-Means Clustering Clustering Base
k-Nearest Neighbor Classification class
Lasso Classification, Regression glmnet
Linear Regression Classification, Regression Base
Logistic Regression Classification Base
Model-Based Clustering Clustering mclust
Naïve Bayes Classification e1071 or klaR
Neural Networks Classification, Regression nnet
Random Forest Classification, Regression randomForest
Ridge Regression Classification, Regression MASS or ridge
Spectral Clustering Clustering kernlab
Support Vector Machine Classification, Regression e1071 or kernlab
Linear Discriminant Analysis Classification MASS
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