Dear All,
I am learning the ropes of CARET for automatic model training, more or
less following the steps of the tutorial at
http://bit.ly/ZJQINa
However, there are a few things about which I would like a piece of
advice.
Consider for instance the following model
#############################################################
set.seed(825)
fitControl <- trainControl(## 10-fold CV
method = "repeatedcv",
number = 10,
## repeated ten times
repeats = 10)
gbmGrid <- expand.grid(interaction.depth = c(1, 5, 9),
n.trees = (1:30)*50,
shrinkage = 0.05)
nrow(gbmGrid)
gbmFit <- train(Ca+P+pH+SOC+Sand~ ., data = training,
method = "gbm",
trControl = fitControl,
## This last option is actually one
## for gbm() that passes through
verbose = TRUE,
## Now specify the exact models
## to evaludate:
tuneGrid = gbmGrid
)
#############################################################
I am trying to tune a model that predicts the values of 5 columns
whose names are "Ca","P","pH", "SOC", and "Sand".
1) Am I using the formula syntax in a correct way?
I then try to apply my model on the test data by coding
mypred <- predict(gbmFit, newdata=test)
However, at this point I am left with a couple of questions
2) does "predict" automatically select the best tuned model in gbmFit?
and if not, what am I supposed to do?
3) I do not get any error messages, but mypred consists of a single
column instead of 5 columns corresponding to the 5 variables I am
trying to predict, so something is obviously wrong (see point 1). Any
suggestions here?
Many thanks
Lorenzo
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
