added precision, recall, f1_score

R/binary_classification.R

@@ -76,3 +76,44 @@ ll <- function(actual, predicted) {
 logLoss <- function(actual, predicted) {
     return(mean(ll(actual, predicted)))
 }
+
+
+
+#' Precision
+#' 
+#' \code{precision} computes proportion of predicted 1's that are actual 1's
+#' @export
+#' @examples 
+#' actual <- c(1, 1, 1, 0, 0, 0)
+#' predicted <- c(1, 1, 1, 1, 1, 1)
+#' precision(actual, predicted)
+precision <- function(actual, predicted) {
+  return(mean(actual[predicted == 1]))
+}
+
+#' Recall
+#' 
+#' \code{recall} computes proportion of actual 1's that are predicted 1's
+#' @export
+#' @examples 
+#' actual <- c(1, 1, 1, 0, 0, 0)
+#' predicted <- c(1, 0, 1, 1, 1, 1)
+#' recall(actual, predicted)
+recall <- function(actual, predicted) {
+  return(mean(predicted[actual == 1]))
+}
+
+#' F1 score
+#' 
+#' \code{f1_score} computes the f1 score
+#' @export
+#' @seealso \code{\link{precision}}, \code{\link{recall}}
+#' @examples 
+#' actual <- c(1, 1, 1, 0, 0, 0)
+#' predicted <- c(1, 0, 1, 1, 1, 1)
+#' recall(actual, predicted)
+f1_score <- function(actual, predicted, beta = 1) {
+  prec = precision(actual, predicted)
+  rec = recall(actual, predicted)
+  return((1 + beta^2) * prec * rec / ((beta^2 * prec) + rec))
+}

tests/testthat/test-binary_classification.R

@@ -21,3 +21,21 @@ test_that('mean los loss is calculated correctly', {
     expect_equal(logLoss(c(1,1,1,0,0,0),c(.5,.1,.01,.9,.75,.001)), 1.881797068998267)
 })
 
+test_that('precision is calculated correctly', {
+    expect_equal(precision(c(1,1,0,0),c(1,1,0,0)), 1)
+    expect_equal(precision(c(0,0,1,1),c(1,1,0,0)), 0)
+    expect_equal(precision(c(1,1,0,0),c(1,1,1,1)), 1/2)
+})
+
+test_that('recall is calculated correctly', {
+  expect_equal(recall(c(1,1,0,0),c(1,1,0,0)), 1)
+  expect_equal(recall(c(0,0,1,1),c(1,1,0,0)), 0)
+  expect_equal(recall(c(1,1,1,1),c(1,0,0,1)), 1/2)
+})
+
+test_that('f1 score is calculated correctly',{
+  expect_equal(f1_score(c(1,1,0,0),c(1,1,0,0)), 1)
+  expect_equal(f1_score(c(0,0,1,1),c(1,1,1,0)), 2/5)
+  expect_equal(f1_score(c(1,1,1,1),c(1,0,0,1)), 2/3)
+})
+