Hi all,
I have a large data set and want to immediately build a 'blind' model
without first examining the data. Now it appears in the data there are a lot
of fields that are constant or all missing values - which prevents the model
from being built.
Can someone point me the right direction as to how I can automatically purge
my data file of these useless fields.
Thanks in advance,
pdb
train <- read.csv("TrainingData.csv")
library(gbm)
i.gbm<-gbm(TargetVariable ~ . ,data=train,distribution="bernoulli.....
1: In gbm.fit(x, y, offset = offset, distribution = distribution, ... :
variable 5: var1 has no variation.
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