Well, the error message seems relatively straightforward.
When you run str(x) (you did not provide the data)
you should see 1 or more components are factors that have more than 32
levels. Apparently you can't include those predictors in a call
to randomForest.
You might find the following line of code useful:
which(sapply(x, function(y) nlevels(y) > 32))
Mai Dang wrote:
I received this error
Error in randomForest.default(m, y, ...) :
Can not handle categorical predictors with more than 32 categories.
using below code
library(randomForest)
library(MASS)
memory.limit(size=12999)
x <- read.csv("D:/train_store_title_view.csv", header=TRUE)
x <- na.omit(x)
set.seed(131)
sales.rf <- randomForest(sales ~ ., data=x, mtry=3,
importance=TRUE)
My machine (i7) running on 64 bit R with 12 gigs of RAM.
Would anyone know how to avoid this error ?
Thank You for your reply,
Mai Dang
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