How can one see in a Boosted trees classification model, which variables interact with each other and how much? I would like to make use o this in R gbm package if possible
From this tutorial. See section 8 in particular.
Look up ?gbm.interactions. First construct your model, named angaus.tc5.lr005 in the tutorial.
angaus.tc5.lr005 <- gbm.step(data=Anguilla_train, gbm.x = 3:13, gbm.y = 2,
+ family = "bernoulli", tree.complexity = 5,
+ learning.rate = 0.005, bag.fraction = 0.5)
Then you will calculate the interactions in the model:
find.int <- gbm.interactions(angaus.tc5.lr005)
After this, you can access multiple attributes of your interaction, including the strength (
$interaction) and the rank (
Have a look through the tutorial, I think it will answer most of your questions. I did not write it.
Edit: This may be out of date as of at least May 2018, please see the comments below.