问题
Is there a standard (or available) way to export a gbm model in R? PMML would work, but when I I try to use the pmml library, perhaps incorrectly, I get an error:
For example, my code looks similar to this:
library("gbm")
library("pmml")
model <- gbm(
formula,
data = my.data,
distribution = "adaboost",
n.trees = 450,
n.minobsinnode = 10,
interaction.depth = 4, shrinkage=0.05, verbose=TRUE)
export <- pmml(model)
# and then export to xml
And the error I get is:
Error in UseMethod("pmml") : no applicable method for 'pmml' applied to an object of class "gbm"
I've also tried passing in the dataset. In any case, I could live with another format I can parse programmatically (I'll be scoring on the JVM) but PMML would be great if there is a way to make that work.
回答1:
You can do the job using the r2pmml package. Currently, it supports regression (ie. distribution = "gaussian"
) and binary classification (ie. distribution = "adaboost"
or distribution = "bernoulli"
) model types.
Below is a sample code for the Auto MPG dataset:
library("gbm")
library("r2pmml")
auto = read.csv(file = "AutoNA.csv", header = TRUE)
auto.formula = gbm(mpg ~ ., data = auto, interaction.depth = 3, shrinkage = 0.1, n.trees = 100, response.name = "mpg")
print(auto.formula)
r2pmml(auto.formula, "/tmp/gbm.pmml")
来源:https://stackoverflow.com/questions/26310836/how-can-i-export-a-gbm-model-in-r