59 lines
1.9 KiB
R
59 lines
1.9 KiB
R
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context("Test deterministic forests")
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test_that("Two forests produce identical results", {
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x1 <- rnorm(100)
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x2 <- rnorm(100)
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y <- 1 + x1 + x2 + rnorm(100)
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data <- data.frame(x1, x2, y)
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forest1 <- train(y ~ x1 + x2, data,
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ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5,
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randomSeed=5)
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forest2 <- train(y ~ x1 + x2, data,
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ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5,
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randomSeed=5)
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newData <- data.frame(x1=rnorm(10), x2=rnorm(10))
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predictions1 <- predict(forest1, newData)
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predictions2 <- predict(forest2, newData)
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expect_equal(round(predictions1, digits=6), round(predictions2, digits=6))
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})
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test_that("Finishing an interrupted forest produces the same results as having finished it", {
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expect_false(file.exists("trees_deterministic_forests")) # Folder shouldn't exist yet
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x1 <- rnorm(1000)
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x2 <- rnorm(1000)
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y <- 1 + x1 + x2 + rnorm(1000)
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data <- data.frame(x1, x2, y)
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forest1 <- train(y ~ x1 + x2, data,
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ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5,
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randomSeed=6)
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forest2.incomplete <- train(y ~ x1 + x2, data,
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ntree=50, numberOfSplits = 5, mtry = 1, nodeSize = 5,
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randomSeed=6, savePath="trees_deterministic_forests")
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forest2.complete <- train(y ~ x1 + x2, data,
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ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5,
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randomSeed=6, savePath="trees_deterministic_forests",
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savePath.overwrite="merge")
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newData <- data.frame(x1=rnorm(10), x2=rnorm(10))
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predictions1 <- predict(forest1, newData)
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predictions2 <- predict(forest2.complete, newData)
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expect_equal(round(predictions1, digits=6), round(predictions2, digits=6))
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unlink("trees_deterministic_forests", recursive=TRUE)
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})
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