In R, we can handle errors with try() and inherits(object-name,'try-error').
mtry <- try(tuneRF(dt[, -3], dat3[,3], ntreeTry=100, stepFactor=1.5,improve=0.01))
if (!inherits(mtry, "try-error")) {
best.m <- mtry[mtry[, 2] == min(mtry[, 2]), 1]
rf <- randomForest(ID~.,data=dt, mtry=best.m, importance=TRUE, ntree=1000)
} else {
rf <- randomForest(ID~.,data=dt, importance=TRUE, ntree=1000)
}
About Author:
Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he has worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and Human Resource.
Very usefull. Thanx. Will greatly benefit from these pages.
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