These data concern amyotrophic lateral sclerosis (Lou Gerig's
disease).
There are 1822 observations on individuals with ALS.
The goal is to predict the rate of progression dFRS of a
functional rating score, using 369 predictors based on measurements
(and derivatives of these) obtained from patient visits.
The first variable in the file is testset, a logical
variable indicating our devision into a training (FALSE) and a test (TRUE)
set.
The next variable dFRS is the response, and the remaining
columns are predictors.
These data were kindly provided by Lester Mackey
and Lilly Fang, who won the DREAM challenge prediction prize in 2012
(Kuffner et al., 2015).
It includes some additional variables created by
them.
Their winning entry used Bayesian trees, not too different from random
forests.
These data can be read directly into R via the command
als <- read.table("http://hastie.su.domains/CASI_files/DATA/ALS.txt",header=TRUE)