Joel Therrien
fdc708dad5
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.
38 lines
No EOL
1.1 KiB
R
38 lines
No EOL
1.1 KiB
R
context("Train and predict with NAs") # previously model.frame removed NAs, causing the responses and covariates to not match up
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test_that("Competing Risks doesn't crash", {
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sampleData <- data.frame(x=rnorm(100))
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sampleData$Time <- rexp(100) + abs(sampleData$x)
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sampleData$delta <- sample(0:2, size = 100, replace=TRUE)
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sampleData$x[50:55] <- NA
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testData <- sampleData[1:5,]
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trainingData <- sampleData[6:100,]
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forest <- train(CR_Response(delta, Time) ~ x, trainingData, ntree=50, numberOfSplits=0, mtry=1, nodeSize=5, cores=2, displayProgress=FALSE)
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predictions <- predict(forest, testData)
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expect_true(T) # show Ok if we got this far
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})
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test_that("Regresssion doesn't crash", {
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sampleData <- data.frame(x=rnorm(100))
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sampleData$y <- rexp(100) + sampleData$x
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sampleData$x[50:55] <- NA
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testData <- sampleData[1:5,]
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trainingData <- sampleData[6:100,]
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forest <- train(y ~ x, trainingData, ntree=50, numberOfSplits=0, mtry=1, nodeSize=5, cores=2, displayProgress=FALSE)
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predictions <- predict(forest, testData)
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expect_true(T) # show Ok if we got this far
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}) |