When choosing the hyperparameters for Generalized Boosted Regression Models, two important choices are shrinkage and the number of trees. Generally a smaller shrinkage with more trees produces a better model, but the modeling time significantly increases. Building a model with too many trees that are heavily cut back by cross ... [Read more...]

This graph and R code compares the exact vs. normal approximations for 95% binomial confidence intervals for n trials with either one success or 50% success. Continue reading → [Read more...]

Here's a simple way to make a bar plot with error bars three ways: standard deviation, standard error of the mean, and a 95% confidence interval. The key step is to precalculate the statistics for ggplot2. Continue reading → [Read more...]

Here is code to calculate RMSE and MAE in R and SAS. RMSE (root mean squared error), also called RMSD (root mean squared deviation), and MAE (mean absolute error) are both used to evaluate models. MAE gives equal weight to all errors, while RMSE gives extra weight to large errors. ... [Read more...]

This R function uses the free freegeoip.net geocoding service to resolve an IP address (or a vector of them) into country, region, city, zip, latitude, longitude, area and metro codes. Continue reading → [Read more...]

After R is done running a long process, you may need to notify the operator to check the R console and provide the next commands. Without installing any more software or creating any batch files or VBS scripts, here is a simple way to create the popup notice in Windows ... [Read more...]

When applying the stats::lag() function to a data frame, you probably expect it will pad the missing time periods with NA, but lag() doesn’t. For example: Nothing happened. Here is an alternative lag function made for this situation. It pads … Continue reading → [Read more...]

nnet2sas() version 1 introduced a way to export a nnet() model trained in R to Base SAS through metaprogramming, and now nnet2sas() version 2 introduces support for variable centering and scaling as implemented in caret::train(). See the link for version … Continue reading → [Read more...]

In R we’ll generate similar continuous distributions for two groups and give a brief overview of statistical tests and visualizations to compare the groups. Though the fake data are normally distributed, we use methods for various kinds of continuous distributions. … Continue reading → [Read more...]

This R code draws individual growth plots as shown in “Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence” by Judith D. Singer and John B. Willett, an excellent book on multilevel modeling and survival analysis. This code recreates figure … Continue reading → [Read more...]

Some R code designed for ggplot2 0.8.9 is not compatible with ggplot2 0.9.0, and today the ggplot2 web site has outdated documentation which gives this broken example: Dennis Murphy points to the ggplot2 0.9.0 transition guide from where I derived … Continue reading → [Read more...]

If you do parallel processing in R on Windows, then you probably have heard of the doSMP package. However, it was recently removed from the CRAN repository with the terse message: Package ‘doSMP’ was removed from the CRAN repository. Revolution … Continue reading → [Read more...]

Artificial neural networks are commonly thought to be used just for classification because of the relationship to logistic regression: neural networks typically use a logistic activation function and output values from 0 to 1 like logistic regression. However, the worth … Continue reading → [Read more...]

This R code fits an artificial neural network in R and generates Base SAS code, so new records can be scored entirely in Base SAS. This is intended to be a simple, elegant, fast solution. You don’t need SAS Enterprise … Continue reading → [Read more...]

This code shows how to easily plot a beautiful confidence interval diagram in R. First, let’s input the raw data. We’ll be making two confidence intervals for two samples of 10. In case you curious, the data represents samples from … Continue reading → [Read more...]

This code creates a decision tree model in R using party::ctree() and prepares the model for export it from R to Base SAS, so SAS can score new records. SAS Enterprise Miner and PMML are not required, and Base SAS … Continue reading → [Read more...]

Let’s walk through using R and Student’s t-test to compare paired sample data. The book Statistics: The Exploration & Analysis of Data (6th edition, p505) presents the longitudinal study “Bone mass is recovered from lactation to postweaning in adolescent mothers … Continue reading → [Read more...]

ggplot2 is a package for R which easily draws plots that are easier on the eyes than R’s built-in plotting functions, though the grammar is different than what is commonly used in R. This code demonstrates how to prepare a … Continue reading → [Read more...]

The same excellent documentation for R commands is available through two different help browsers: text and HTML, and let’s see how how each looks, works, and how to switch the default. Look and feel Here is how both look for … Continue reading → [Read more...]

Usually data mining benchmarks measure lift, precision, etc., but wasting analyst time hurts the ROI of any project. I recently upgraded my notebook (where I often use R for data mining) and was faced with two questions: for the fastest … Continue reading → [Read more...]