v2.18.6

datarobot/DESCRIPTION

@@ -1,6 +1,6 @@
 Package: datarobot
 Title: 'DataRobot' Predictive Modeling API
-Version: 2.18.5
+Version: 2.18.6
 Description: For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.
 Depends: R (>= 3.5), methods, stats
 Imports: httr (>= 1.2.0), jsonlite (>= 1.0), yaml (>= 2.1.19)
@@ -28,6 +28,6 @@ Suggests: lubridate, knitr, testthat, lintr, data.table, AmesHousing,
 VignetteBuilder: knitr
 RoxygenNote: 7.2.3
 NeedsCompilation: no
-Packaged: 2023-10-30 22:37:09 UTC; aj
+Packaged: 2024-03-13 19:51:54 UTC; aj
 Language: en-US
 Config/testthat/edition: 2

datarobot/NEWS.md

@@ -1,8 +1,16 @@
+# datarobot v2.18.6
+
+This is a maintenance release to ensure package compatibility with future versions of R.
+
+* Fixed a small issue with the metadata for the "Introduction to Multiclass" vignette.
+* Fixed some outstanding code formatting issues in various roxygen docs.
+
 # datarobot v2.18.5
 
 This is a maintenance release.
 
 Bugfixes:
+
 * The functions `ListProjects` now has NULL default values for `limit` and `offset` arguments to maintain backwards compatibility. This fixes compatibility issues with versions of DataRobot before 9.x.
 
 # datarobot v2.18.4

datarobot/R/Enums.R

@@ -419,8 +419,9 @@ MulticlassDeploymentAccuracyMetric <- namedEnumList(c(
 #'
 #' All possible deployment accuracy metrics. Added in DataRobot API 2.18.
 #'
-#' For usage, see `\code{DeploymentAccuracy} and `code{DeploymentAccuracyOverTime}.
+#' For usage, see `DeploymentAccuracy` and `DeploymentAccuracyOverTime`.
 #' @export
+#' @md
 DeploymentAccuracyMetric <- {
   # Combine and dedupe the different metric types
   DeploymentAccuracyMetric <- c(

datarobot/R/GetPredictions.R

@@ -121,7 +121,7 @@ SelectDesiredPredictions <- function(parsedPredictionResponse, type, classPrefix
 #' The contents of the return vector depends on the modeling
 #' task - binary classification, multiclass classification, or regression;
 #' whether or not the underlying data is time series, multiseries, cross-series, or not
-#' time series; and the value of the /code{type} parameter. For non-time-series regression tasks,
+#' time series; and the value of the \code{type} parameter. For non-time-series regression tasks,
 #' the type parameter is ignored and a vector of numerical predictions of the response
 #' variable is returned.
 #'

datarobot/R/ListModelJobs.R

@@ -68,7 +68,7 @@ ListModelJobs <- function(project, status = NULL) {
 #' @return list with following elements:
 #' \itemize{
 #'   \item status character. Model job status; an element of \code{JobStatus}, e.g.
-#'     \code{JobStatus$Queue.}
+#'     \code{JobStatus$Queue}.
 #'   \item processes list. List of character vectors describing any preprocessing applied.
 #'   \item projectId character. The unique identifier for the project.
 #'   \item modelId character. The unique identifier for the related model.
@@ -77,7 +77,7 @@ ListModelJobs <- function(project, status = NULL) {
 #'     the model.
 #'   \item modelType character. string specifying the model this job builds.
 #'   \item modelCategory character. What kind of model this is - \code{prime} for DataRobot Prime
-#'     models, /code{blend} for blender models, and /code{model} for other models.
+#'     models, \code{blend} for blender models, and \code{model} for other models.
 #'   \item featurelistId character. Id of the featurelist used in fitting the model.
 #'   \item blueprintId character. Id of the DataRobot blueprint on which the model is based.
 #'   \item modelJobId character. Id of the job.

datarobot/R/MultiSeries.R

@@ -167,7 +167,7 @@ RequestMultiSeriesDetection <- function(project, dateColumn, multiseriesIdColumn
 #'
 #' Note that this function no longer needs to be called directly, but is called
 #' indirectly as a part of \code{SetTarget} (which itself is called indirectly as part of
-#' \code{StartProject}) when you pass a /code{crossSeriesGroupByColumn} using
+#' \code{StartProject}) when you pass a \code{crossSeriesGroupByColumn} using
 #' \code{CreateDatetimePartitionSpecification}.
 #'
 #' @inheritParams RequestMultiSeriesDetection

datarobot/R/PredictionDatasets.R

@@ -267,7 +267,7 @@ DeletePredictionDataset <- function(project, datasetId) {
 #' Request predictions from a model against a previously uploaded dataset
 #'
 #' Prediction intervals can now be returned for predictions with datetime models.
-#' Use `includePredictionIntervals = TRUE` in calls to /code{Predict} or /code{RequestPredictions}.
+#' Use `includePredictionIntervals = TRUE` in calls to \code{Predict} or \code{RequestPredictions}.
 #' For each model, prediction intervals estimate the range of values DataRobot expects actual values
 #' of the target to fall within. They are similar to a confidence interval of a prediction, but are
 #' based on the residual errors measured during the backtesting for the selected model.

datarobot/R/Projects.R

@@ -40,8 +40,10 @@ DeleteProject <- function(project) {
 #' @param filter list. Optional. A named list that can be used to specify various filters.
 #'  Currently `projectName` is supported which will filter returned projects for projects with
 #'  names containing the specified string.
-#' @param limit integer. Optional. At most this many results are returned. Invoking `ListProjects` with this value against DataRobot 8.x (API 2.28) or older will throw an error.
-#' @param offset integer. Optional. This many results will be skipped. Invoking `ListProjects` with this value against DataRobot 8.x (API 2.28) or older will throw an error.
+#' @param limit integer. Optional. At most this many results are returned. Invoking `ListProjects`
+#'  with this value against DataRobot 8.x (API 2.28) or older will throw an error.
+#' @param offset integer. Optional. This many results will be skipped. Invoking `ListProjects` with
+#'  this value against DataRobot 8.x (API 2.28) or older will throw an error.
 #'
 #' @return An S3 object of class 'projectSummaryList', consisting of the following elements:
 #' \itemize{
@@ -82,7 +84,8 @@ DeleteProject <- function(project) {
 #' @export
 ListProjects <- function(filter = NULL, limit = NULL, offset = NULL) {
   routeString <- "projects/"
-  # We do not automatically pass the limit and offset arguments to ensure backwards compatibility for DataRobot < 9.0
+  # We do not automatically pass the limit and offset arguments to ensure backwards compatibility
+  # for DataRobot < 9.0
   params <- list()
   params$limit <- limit
   params$offset <- offset

datarobot/R/StartRetryWaiter.R

@@ -7,10 +7,10 @@
 #' @param delay integer. Initial delay between tries (in seconds).
 #' @param maxdelay integer. Maximum delay (in seconds) between tries.
 #' @return function which gets the waiter status. This function returns a list with these items:
-#' /itemize{
-#'    /item index numeric. How many times we have waited.
-#'    /item secondsWaited numeric. How long (in seconds) since we started the timer.
-#'    /item stillTrying logical. Whether we should keep trying or give up (logical)
+#' \itemize{
+#'   \item index numeric. How many times we have waited.
+#'   \item secondsWaited numeric. How long (in seconds) since we started the timer.
+#'   \item stillTrying logical. Whether we should keep trying or give up (logical)
 #' }
 StartRetryWaiter <- function(timeout = NULL, delay = .1, maxdelay = 1.0) {
   if (is.null(timeout)) {

datarobot/inst/doc/AdvancedTuning.html

@@ -12,7 +12,7 @@
 
 <meta name="author" content="Peter Hurford" />
 
-<meta name="date" content="2023-10-30" />
+<meta name="date" content="2024-03-13" />
 
 <title>Advanced Tuning for Models</title>
 
@@ -31,23 +31,23 @@
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@@ -340,7 +341,7 @@
 
 <h1 class="title toc-ignore">Advanced Tuning for Models</h1>
 <h4 class="author">Peter Hurford</h4>
-<h4 class="date">2023-10-30</h4>
+<h4 class="date">2024-03-13</h4>