Add bestSpecificLearner

DESCRIPTION

@@ -23,6 +23,7 @@ Depends: R (>= 3.6.0)
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
 Collate: 
+    'BestSpecificLearner.R'
     'Data.R'
     'HashTable.R'
     'Lrner.R'
@@ -46,4 +47,5 @@ Collate:
     'VarSel.R'
     'entities.R'
     'weightedMeanLearner.R'
+    'predict.bestSpecificLearner.R'
     'predict.weightedMeanLearner.R'

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(predict,bestSpecificLearner)
 S3method(predict,weightedMeanLearner)
 export(Data)
 export(HashTable)
@@ -22,6 +23,7 @@ export(TrainLayer)
 export(TrainMetaLayer)
 export(Training)
 export(VarSel)
+export(bestSpecificLearner)
 export(weightedMeanLearner)
 importFrom(R6,R6Class)
 importFrom(digest,digest)

tests/testthat/test-bestSpecificLearner.R

@@ -0,0 +1,36 @@
+test_that("bestSpecificLearner works", {
+  expect_no_error({
+    set.seed(20240624L)
+    x = data.frame(x1 = runif(n = 50L, min = 0, max = 1))
+    y = sample(x = 0L:1L, size = 50L, replace = TRUE)
+    my_model = bestSpecificLearner(x = x, y = y)
+    x_new <- data.frame(x1 = rnorm(10))
+    my_predictions <- predict(object = my_model, data = x_new)
+  })
+  expect_error({
+    set.seed(20240624L)
+    x = data.frame(x1 = runif(n = 50L, min = 0, max = 1))
+    y = sample(x = 0L:1L, size = 50L, replace = TRUE)
+    my_model = bestSpecificLearner(x = x, y = y)
+    x_new <- data.frame(x2 = rnorm(10))
+    my_predictions <- predict(object = my_model, data = x_new)
+  })
+  expect_error({
+    set.seed(20240624L)
+    x = data.frame(x1 = runif(n = 50L, min = 0, max = 1))
+    y = sample(x = 0L:2L, size = 50L, replace = TRUE)
+    my_model = bestSpecificLearner(x = x, y = y)
+  })
+  expect_no_error({
+    set.seed(20240624L)
+    x = data.frame(x1 = runif(n = 50L, min = 0, max = 1))
+    y = factor(sample(x = c("control", "case"), size = 50L, replace = TRUE))
+    my_model = bestSpecificLearner(x = x, y = y)
+  })
+  expect_no_error({
+    set.seed(20240624L)
+    x = data.frame(x1 = runif(n = 50L, min = 0, max = 1))
+    y = sample(x = c("0", "1"), size = 50L, replace = TRUE)
+    my_model = bestSpecificLearner(x = x, y = factor(y))
+  })
+})