Ginger Grant has a list of machine learning algorithms and their implementations in R:
Often times determining which algorithm to use can take a while. Here is a pretty good flowchart for determining which algorithm should be used given some examples of what the desired outcomes and data contain. The diagram lists the algorithms, which are implemented in Azure ML. The same algorithms can be implemented in R. In R there are libraries to help with nearly every task. Here’s a list of libraries and their accompanying links which can be used in Machine Learning. This list is no means comprehensive as there are libraries and functions other than the ones listed here, but if you are trying to write a Machine Learning Experiment in R, and are looking at the flowchart, these R functions and Libraries will provide the tools to do the types of Machine Learning Analysis listed.
I think algorithm determination is one of the most difficult parts of machine learning. Even if you don’t mean to go there, the garden of forking paths is dangerous.