AppleGate0 - 1 month ago 11

R Question

I am trying to tune parameters using the caret package in R but get a

`Error in train.default(x = as.matrix(df_train %>% select(-c(Response, :`

The tuning parameter grid should have columns nrounds, lambda, alpha

whenever I try to train the model, even though the columns nrounds, lambda, and alpha are there.

`library(caret)`

library(xgboost)

library(readr)

library(dplyr)

library(tidyr)

xgb_grid_1 <- expand.grid(

nrounds= 2400,

eta=c(0.01,0.001,0.0001),

lambda = 1,

alpha =0

)

xgb_trcontrol <- trainControl(

method="cv",

number = 5,

verboseIter = TRUE,

returnData=FALSE,

returnResamp = "all",

allowParallel = TRUE,

)

xgb_train_1 <- train(

x = as.matrix(df_train %>% select(-c(Response, Id))),

y= df_train$Response,

trControl = xgb_trcontrol,

tuneGrid = xgb_grid_1,

method="xgbLinear"

)

Answer

The problem lies in your xgb_grid_1. If you remove the line eta it will work.

Standard tuning options with xgboost and caret are "nrounds", "lambda" and "alpha". Not eta. use the modelLookup function to see which model parameters are available. If you want to use eta as well, you will have to create your own caret model to use this extra parameter in tuning as well.

```
modelLookup("xgbLinear")
model parameter label forReg forClass probModel
1 xgbLinear nrounds # Boosting Iterations TRUE TRUE TRUE
2 xgbLinear lambda L2 Regularization TRUE TRUE TRUE
3 xgbLinear alpha L2 Regularization TRUE TRUE TRUE
```

Source (Stackoverflow)

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