This package illustrates how to deploy a model for remote scoring/prediction.
# Install in R
library(devtools)
install_github("opencpu/tvscore")
# Score in R
library(tvscore)
mydata <- data.frame(
age=c(24, 54, 32, 75),
marital=c("MARRIED", "DIVORCED", "WIDOWED", "NEVER MARRIED")
)
tv(input = mydata)
# Score remotely
curl https://public.opencpu.org/ocpu/github/opencpu/tvscore/R/tv/json \
-H "Content-Type: application/json" \
-d '{"input" : [ {"age":26, "marital" : "MARRIED"}, {"age":41, "marital":"DIVORCED"} ]}'
The model is included in the data directory of the package, and was created
using the createmodel.R script. It predicts hours per day of TV watching from age and marital status. The model looks like this:
