randomForest speed improvements

[image removed] 

[R] randomForest speed improvements

apresley 

to:

r-help

01/03/2011 03:03 PM

Sent by:

r-help-bounces at r-project.org


Hi there,

We're trying to use randomForest to do some predictions.  The 

for our code is pretty straightforward:

  library ('randomForest');
  data202 <- read.csv ("random.csv", header=TRUE);
  x<- data202[1:50000,1:6];
  y<- data202[1:50000,8];
  y<- y[,drop=TRUE];

  x2 <- data202[50001:60000,1:6];
  y2 <- data202[50001:60000,8];
  y2 <- y2[,drop=TRUE];

  RFobject <- randomForest(x,y,na.action=na.roughfix);
  p <- predict (RFobject, x2);

In this case, the CSV contains 10 columns, of which 1-6 are numeric in
nature (day of week, week of month, etc...) and column 8 is the target
(sales, a numeric number).

randomForest does fine with the data, our issue is how long it takes. In
this case, about 5,000 rows of data seems to take just a few seconds, 

going to 50,000 rows doesn't take 5x the time, it takes perhaps 30 or 40
minutes.

We've downloaded and tried RT-Rank, which is a multi-threaded version of
RandomForest, and this seems to produce the same (or slightly better)
predictions, but also gets done fairly quickly.

What can we do to improve the speed of this data computation?  The 

we're on is a dual quad-core Intel CPU @ 2.33Ghz, and with 16GB of RAM 

we're using the "stock" R RPM for CentOS 5.5.

Thanks!

--
Anthony
-- 
View this message in context: http://r.789695.n4.nabble.com/
randomForest-speed-improvements-tp3172523p3172523.html
Sent from the R help mailing list archive at Nabble.com.