library("regressoR")
context("regressoR.defaultLearners")
test_that("Test regressoR.defaultLearners()", {
learners <- regressoR.defaultLearners();
expect_true(!is.null(learners));
expect_true(is.list(learners));
expect_gt(length(learners), 0L);
x <- runif(n=10, min=1, max=10);
params <- c(5, 7);
func <- function(x) { params[1] + params[2]*x };
y <- func(x);
metric <- regressoR.quality::RegressionQualityMetric.default(x, y);
for(learner in learners) {
expect_true(is.function(learner));
result <- learner(metric, NULL, NULL, NULL, q=0.76);
expect_true(!is.null(result));
expect_is(result, "FittedModel");
validObject(result);
}
})
test_that("Test regressoR.monotonousLearners()", {
learners <- regressoR.monotonousLearners();
expect_true(!is.null(learners));
expect_true(is.list(learners));
expect_gt(length(learners), 0L);
x <- runif(n=10, min=1, max=10);
params <- c(5, 7);
func <- function(x) { params[1] + params[2]*x };
y <- func(x);
metric <- regressoR.quality::RegressionQualityMetric.default(x, y);
for(learner in learners) {
expect_true(is.function(learner));
result <- learner(metric, NULL, NULL, NULL, q=0.76);
expect_true(!is.null(result));
expect_is(result, "FittedModel");
validObject(result);
}
})
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