Nothing
test_that("PredictionDataClassif", {
task = tsk("iris")
learner = lrn("classif.featureless", predict_type = "prob")
p = learner$train(task)$predict(task)
pdata = p$data
expect_s3_class(pdata, "PredictionDataClassif")
expect_integer(pdata$row_ids, any.missing = FALSE)
expect_factor(pdata$truth, levels = task$class_names, any.missing = FALSE)
expect_factor(pdata$response, levels = task$class_names, any.missing = FALSE)
expect_matrix(pdata$prob, nrows = task$nrow, ncols = length(task$class_names), any.missing = FALSE)
expect_s3_class(c(pdata, pdata), "PredictionDataClassif")
expect_prediction(as_prediction(pdata))
expect_equal(as.data.table(p), as.data.table(as_prediction(pdata)))
pdata = filter_prediction_data(pdata, row_ids = 1:3)
expect_set_equal(pdata$row_ids, 1:3)
expect_factor(pdata$truth, len = 3)
expect_factor(pdata$response, len = 3)
expect_matrix(pdata$prob, nrows = 3)
})
test_that("row sums of prob sums up to 1 ", {
pdata = new_prediction_data(list(row_ids = 1:2, truth = factor(c("a", "b")),
response = c("a", "b"), prob = matrix(c(0.5, 0.5, 0.5, 1), 2)), "classif")
expect_error(check_prediction_data(pdata), "sum up")
})
test_that("construction of empty PredictionDataClassif", {
task = tsk("iris")
learner = lrn("classif.featureless")
learner$train(task)
pred = learner$predict(task, row_ids = integer())
expect_prediction(pred)
expect_set_equal(pred$predict_types, "response")
expect_integer(pred$row_ids, len = 0L)
expect_factor(pred$truth, len = 0L, levels = task$class_names)
expect_null(pred$prob)
expect_data_table(as.data.table(pred), nrows = 0L, ncols = 3L)
learner = lrn("classif.featureless", predict_type = "prob")
learner$train(task)
pred = learner$predict(task, row_ids = integer())
expect_prediction(pred)
expect_set_equal(pred$predict_types, c("response", "prob"))
expect_integer(pred$row_ids, len = 0L)
expect_factor(pred$truth, len = 0L, levels = task$class_names)
expect_matrix(pred$prob, nrows = 0L, ncols = length(task$class_names))
expect_data_table(as.data.table(pred), nrows = 0L, ncols = 6L)
})
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