Skip to content

Commit

Permalink
measures: Small changes of the texts in the note section (#1803)
Browse files Browse the repository at this point in the history
  • Loading branch information
MinhAnhL authored and berndbischl committed Aug 9, 2017
1 parent 3a320a3 commit ff73723
Show file tree
Hide file tree
Showing 2 changed files with 6 additions and 6 deletions.
10 changes: 5 additions & 5 deletions R/measures.R
Original file line number Diff line number Diff line change
Expand Up @@ -974,7 +974,7 @@ measureFN = function(truth, response, negative) {
tpr = makeMeasure(id = "tpr", minimize = FALSE, best = 1, worst = 0,
properties = c("classif", "req.pred", "req.truth"),
name = "True positive rate",
note = "Percentage of correctly classified observations in the positive class. Also called hit rate or recall.",
note = "Percentage of correctly classified observations in the positive class. Also called hit rate or recall or sensitivity.",
fun = function(task, model, pred, feats, extra.args) {
measureTPR(pred$data$truth, pred$data$response, pred$task.desc$positive)
}
Expand Down Expand Up @@ -1050,7 +1050,7 @@ measureFNR = function(truth, response, negative, positive) {
ppv = makeMeasure(id = "ppv", minimize = FALSE, best = 1, worst = 0,
properties = c("classif", "req.pred", "req.truth"),
name = "Positive predictive value",
note = "Defined as: tp / (tp + number of fp). Also called precision. If the denominator is 0, PPV is set to be either 1 or 0 depending on whether the highest probability prediction is positive (1) or negative (0).",
note = "Defined as: tp / (tp + fp). Also called precision. If the denominator is 0, PPV is set to be either 1 or 0 depending on whether the highest probability prediction is positive (1) or negative (0).",
fun = function(task, model, pred, feats, extra.args) {
if (pred$predict.type == "prob") {
prob = getPredictionProbabilities(pred)
Expand Down Expand Up @@ -1086,7 +1086,7 @@ measureEdgeCase = function(truth, positive, prob) {
npv = makeMeasure(id = "npv", minimize = FALSE, best = 1, worst = 0,
properties = c("classif", "req.pred", "req.truth"),
name = "Negative predictive value",
note = "Defined as: (tn) / (tn + fn).",
note = "Defined as: tn / (tn + fn).",
fun = function(task, model, pred, feats, extra.args) {
measureNPV(pred$data$truth, pred$data$response, pred$task.desc$negative)
}
Expand All @@ -1105,7 +1105,7 @@ measureNPV = function(truth, response, negative) {
fdr = makeMeasure(id = "fdr", minimize = TRUE, best = 0, worst = 1,
properties = c("classif", "req.pred", "req.truth"),
name = "False discovery rate",
note = "Defined as: (fp) / (tn + fn).",
note = "Defined as: fp / (tp + fp).",
fun = function(task, model, pred, feats, extra.args) {
measureFDR(pred$data$truth, pred$data$response, pred$task.desc$positive)
}
Expand All @@ -1124,7 +1124,7 @@ measureFDR = function(truth, response, positive) {
mcc = makeMeasure(id = "mcc", minimize = FALSE,
properties = c("classif", "req.pred", "req.truth"), best = 1, worst = -1,
name = "Matthews correlation coefficient",
note = "Defined as sqrt((tp + fp) * (tp + fn) * (tn + fp) * (tn + fn)), denominator set to 1 if 0",
note = "Defined as (tp * tn - fp * fn) / sqrt((tp + fp) * (tp + fn) * (tn + fp) * (tn + fn)), denominator set to 1 if 0",
fun = function(task, model, pred, feats, extra.args) {
measureMCC(pred$data$truth, pred$data$response, pred$task.desc$negative, pred$task.desc$positive)
}
Expand Down
2 changes: 1 addition & 1 deletion tests/testthat/test_base_measures.R
Original file line number Diff line number Diff line change
Expand Up @@ -356,7 +356,7 @@ test_that("check measure calculations", {
#test multiclass measures

#mmce
mmce.test = mean(c(1L != 1L, 2L != 0L, 0L != 0L, 1L != 2L))
mmce.test = mean(c(1L != 1L, 2L != 1L, 0L != 0L, 1L != 2L))
mmce.perf = performance(pred.classif, measures = mmce, model = mod.classif)
expect_equal(mmce.test, mmce$fun(pred = pred.classif))
expect_equal(mmce.test, as.numeric(mmce.perf))
Expand Down

0 comments on commit ff73723

Please sign in to comment.