Speeding up random forest with R

Live Online Training : Data Science with R

- Explain Advanced Algorithms in Simple English
- Live Projects
- Case Studies
- Job Placement Assistance
- Get 10% off till Oct 26, 2017
- Batch starts from October 28, 2017

If you want to create a random forest model with 500 trees, and your computer has 2 cores, you can execute the randomForest function parallely with 2 cores, with the ntree argument set to 250. and then combine the resulting randomForest objects.
# Installed the required libraries
library("foreach")
library("doSNOW")
library(randomForest)

# Setting number of cores in your machine. In this case, it is 2
registerDoSNOW(makeCluster(2, type="SOCK"))

# Loading data
data(iris)
mydata = iris

# Optimal mtry
mtry <- tuneRF(iris[,-5],iris[,5], stepFactor=0.5)
print(mtry)
best.m <- mtry[mtry[, 2] == min(mtry[, 2]), 1]

# Main Random Forest Code. Run 250 trees on 2 cores parallely and then combine them
rf <- foreach(ntree = rep(250, 2), .combine = combine, .packages = "randomForest") %dopar% randomForest(Species~.,data=mydata,ntree=ntree, mtry=best.m, importance=TRUE)

# Check rf object
rf

# Check variable importance
importance(rf, type=1)
varImpPlot(rf, type=1)
Call:
randomForest(formula = Species ~ ., data = mydata, ntree = ntree, mtry = best.m, importance = TRUE)

Type of random forest: classification
Number of trees: 500
No. of variables tried at each split: 2

R Tutorials : 75 Free R Tutorials


Statistics Tutorials : 50 Statistics Tutorials


Statistics Tutorials : 50 Statistics Tutorials

About Author:

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has close to 7 years of experience in data science and predictive modeling. During his tenure, he has worked with global clients in various domains like retail and commercial banking, Telecom, HR and Automotive.


While I love having friends who agree, I only learn from those who don't.

Let's Get Connected: Email | LinkedIn

Get Free Email Updates :
*Please confirm your email address by clicking on the link sent to your Email*

Related Posts:

0 Response to "Speeding up random forest with R"

Post a Comment

Next → ← Prev