So I have a data set that is essentially football players statistics in 2017 and 2018. I have trained my model to use the 2017 data to predict the 2018 number of touchdowns. My code is below:
set.seed(1) data.rf <- randomForest(2018_td ~ ., data = data, proximity = TRUE)
In my data set, I had the actual # of touchdowns in 2018, and trained a random forest algorithm to predict that value. Now, I want to apply the trained random forest on the same 2018 data set, but to predict 2019 # of TD, that I don't have.
I'm not sure if I'm missing something or if I have a fundamentally wrong understanding of how RF works. How would I go about predicting those 2019 values from my