library(ranger) library(randomForest) test_that('MDI works for ranger & classification tree', { set.seed(42L) rfobj <- ranger(Species ~ ., iris, keep.inbag = TRUE, importance = 'impurity') tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]) iris.MDITree <- MDITree(tidy.RF, 1, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDITree), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDITree), list(names(iris[, -5]), levels(iris$Species))) iris.MDI <- MDI(tidy.RF, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDI), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDI), list(names(iris[, -5]), levels(iris$Species))) expect_equal(as.vector(rowSums(iris.MDI)), as.vector(ranger::importance(rfobj) / sum(tidy.RF$inbag.counts[[1]]))) }) test_that('MDI works for randomForest & classification tree', { set.seed(42L) rfobj <- randomForest(Species ~ ., iris, keep.inbag = TRUE, importance = TRUE) tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]) iris.MDITree <- MDITree(tidy.RF, 1, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDITree), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDITree), list(names(iris[, -5]), levels(iris$Species))) iris.MDI <- MDI(tidy.RF, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDI), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDI), list(names(iris[, -5]), levels(iris$Species))) expect_equal(as.vector(rowSums(iris.MDI)), as.vector(importance(rfobj)[, 'MeanDecreaseGini'] / sum(tidy.RF$inbag.counts[[1]]))) }) test_that('MDIoob works for ranger & classification tree', { set.seed(42L) rfobj <- ranger(Species ~ ., iris, keep.inbag = TRUE) tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]) iris.MDIoobTree <- MDIoobTree(tidy.RF, 1, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDIoobTree), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDIoobTree), list(names(iris[, -5]), levels(iris$Species))) iris.MDIoob <- MDIoob(tidy.RF, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDIoob), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDIoob), list(names(iris[, -5]), levels(iris$Species))) }) test_that('MDIoob works for randomForest & classification tree', { set.seed(42L) rfobj <- randomForest(Species ~ ., iris, keep.inbag = TRUE) tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]) iris.MDIoobTree <- MDIoobTree(tidy.RF, 1, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDIoobTree), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDIoobTree), list(names(iris[, -5]), levels(iris$Species))) iris.MDIoob <- MDIoob(tidy.RF, iris[, -5], iris[, 5]) expect_equal(dim(iris.MDIoob), c(ncol(iris) - 1, nlevels(iris$Species))) expect_equal(dimnames(iris.MDIoob), list(names(iris[, -5]), levels(iris$Species))) }) test_that(paste('MDIoob emits error for ranger & classification tree', 'when keep.inbag = FALSE'), { set.seed(42L) rfobj <- ranger(Species ~ ., iris) expect_warning(tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]), 'keep.inbag = FALSE; all samples will be considered in-bag.') expect_error(MDIoobTree(tidy.RF, 1, iris[, -5], iris[, 5]), 'No out-of-bag data available.') expect_error(MDIoob(tidy.RF, iris[, -5], iris[, 5]), 'No out-of-bag data available.') }) test_that(paste('MDIoob emits error for randomForest & classification tree', 'when keep.inbag = FALSE'), { set.seed(42L) rfobj <- randomForest(Species ~ ., iris) expect_warning(tidy.RF <- tidyRF(rfobj, iris[, -5], iris[, 5]), 'keep.inbag = FALSE; all samples will be considered in-bag.') expect_error(MDIoobTree(tidy.RF, 1, iris[, -5], iris[, 5]), 'No out-of-bag data available.') expect_error(MDIoob(tidy.RF, iris[, -5], iris[, 5]), 'No out-of-bag data available.') })