Setting up random seed is important for reproducibility of analysis. In this post, we discuss how to generate random seed using the caret package.

We discuss how to turn analysis into an R package.

Part II that demonstrates how to implement parallem processing on single machine in R

Part III that demonstrates how to implement parallem processing on single machine in R

Part I that demonstrates how to implement parallem processing on single machine in R

Part VI of tree based methods in R series. Performance of classification analysis is discussed.

Part V of tree based methods in R series. Performance of regression analysis is discussed.

Part IV of tree based methods in R series. 3 R packages for classification analysis are compared - rpart, caret and mlr packages.

Part III of tree based methods in R series. Regression tasks are discussed.

Part II of tree based methods in R series. Cost-sensitive classification is implemented, assuming that misclassifying the High class is twice as expensive, both by altering the priors and by adjusting the loss matrix.