if (FALSE) {
library(h2o)
h2o.init()
f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv"
cars <- h2o.importFile(f)
predictors <- c("displacement", "power", "weight", "acceleration", "year")
response <- "acceleration"
cars_model <- h2o.modelSelection(y=response,
x=predictors,
training_frame = cars,
min_predictor_number=2,
mode="backward",
influence="dfbetas",
lambda=0.0,
family="gaussian")
rid_frame <- h2o.get_regression_influence_diagnostics(cars_model, predictorSize=3)
}
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