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.

Part I of tree based methods in R series. Classification analysis is performed using the caret package.

This is a quick trial of adding overall and conditional (by user) average columns in a data frame.

We discuss how to loop without for in R.

I demonstrate short R examples - summarise a data frame group by a column and a quick way of implementing simulation

This post is a slight extension of the previous two articles - Download Stock Data - Part I and Download Stock Data - Part II. We discuss how to produce gross returns, standard deviation and correlation of multiple shares.

In an earlier article, a way to download stock price data files from Google, save it into a local drive and merge them into a single data frame. If files are not large, however, it wouldn't be effective and, in this article, files are downloaded and merged internally.

This article illustrates how to download stock price data files from Google, save it into a local drive and merge them into a single data frame.