Random Forest, Variable Mismatch
On Sat, Feb 15, 2014 at 8:43 AM, Lorenzo Isella
<lorenzo.isella at gmail.com> wrote:
Dear All,
I am a bit puzzled.
I am developing a random forest model.
The data is large and it involves hundred of predictors, but the code I have
written is relatively simple.
After training my random forest model, I apply it on some new data set to
carry out some prediction, as you can see below
response_validation <- predict(rf,newdata=mydata,
type="response")
but I get this error message
Error in predict.randomForest(rf, newdata = mydata, type = "response") :
variables in the training data missing in newdata
This error is thrown when the column names in original and new data do not agree. Make sure the column names in your original data and the new data 'mydata' are the same.
I am confused because I checked that there is no missing data neither in my training nor in my test data sets and the data types of the columns of both the test and train data sets are perfectly identical.
column types are not enough - the column names must be the same. HTH, Peter