largeRCRF/tests/testthat/test_saving_offline.R
Joel Therrien fdc708dad5 New features -
Add support for making predictions without specifying training data
Add support for adding trees to an existing forest
Add support for toggling displayProgress

Also reduced the size of the package by removing some unused dependency
classes.
2019-06-19 13:15:43 -07:00

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R

context("Make sure we can save forests while training")
test_that("Can save a random forest while training, and use it afterward", {
expect_false(file.exists("trees")) # Folder shouldn't exist yet
x1 <- rnorm(1000)
x2 <- rnorm(1000)
y <- 1 + x1 + x2 + rnorm(1000)
data <- data.frame(x1, x2, y)
forest <- train(y ~ x1 + x2, data,
ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5,
savePath="trees", displayProgress=FALSE)
expect_true(file.exists("trees")) # Something should have been saved
# try making a little prediction to verify it works
newData <- data.frame(x1=seq(from=-3, to=3, by=0.5), x2=0)
predictions <- predict(forest, newData)
# Also make sure we can load the forest too
newforest <- loadForest("trees")
predictions <- predict(newforest, newData)
unlink("trees", recursive=TRUE)
})