If its the actually time to build the models within R that bothers you, what can I say. Machine Learning is not a simple calculation and often involves executing dead and inferior branches that are not part of the eventual solution.

Check your data dimensions.
- typically, modeling time depends on the number of training examples. Use R "sample" method as a sledgehammer for reducing it.
- typically, modeling time depends on the number of features. Detect near-zero-variance features, use covariance matrix to detect identical features, or use advanced feature selection such as recursive feature elimination -- but that has its own cost.