Classification: Description of training data: The training dataset comprises 1,962 data points with 265 dimensional inputs and binary class labels. The training inputs and outputs are available as separate comma separated value (CSV) files. The first row of each CSV file contains the column names and the first column contains the data point index (running from 1 to 1,962).

Regression: Description of training data: The training dataset comprises 33,750 data points with 14 dimensional inputs and one dimensional real-valued outputs.

Density modelling: Description of training data: The dataset comprises 5,000 data points each of 14 dimensions drawn from an unknown probability density. The data are available as a CSV file. The goal is to estimate the log-probability density at each of these points. Note that three of the variables are binary and the rest are real valued.