package refactoring

orionw · Jan 8, 2019 · 70aacee · 70aacee
1 parent 1a48ac7
commit 70aacee
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diff --git a/.RData b/.RData
diff --git a/.Rhistory b/.Rhistory
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,5 +1,5 @@
 Package: BestModel
-Title: A package to run and compare standard machine learning models with easy visualization.
+Title: A package to run and compare standard machine learning models with easy visualization
 Version: 0.0.1.0000
 Authors@R: person("Orion", "Weller", email = "first.last@example.com", role = c("aut", "cre"))
 Description: This package allows for the creation of ModelComparison objects. These objects provide an easy way to visualize the metrics between the different models. You can supply the models yourself, or create them in the function.  It also allows for easy Ensembling as well as other helper functionality.
@@ -8,7 +8,7 @@ License: What license is it under?
 Encoding: UTF-8
 LazyData: true
 Suggests: testthat
-depends:
+Imports:
 	caret,
   pROC,
   ggplot2,

diff --git a/NAMESPACE b/NAMESPACE
@@ -28,6 +28,3 @@ export(PrepareIris)
 export(PrepareNumericTitanic)
 export(StripPredictions)
 export(prepData)
-exportPattern("^[[:alpha:]]+")
-importFrom(Rcpp,evalCpp)
-useDynLib(BestModel)
diff --git a/R/Ensembling.R b/R/Ensembling.R
@@ -8,7 +8,7 @@
 #'
 #' @examples
 #' # This function is used by predict.Ensemble. It's usage is as follows:
-#' preds[[i]] <-  StripPredictions(predict(model, newdata = newdata, type="prob"))
+#' # preds[[i]] <-  StripPredictions(predict(model, newdata = newdata, type="prob"))
 #'
 #' @keywords internal
 #' @export
@@ -29,6 +29,8 @@ StripPredictions <- function(pred) {
 #' Gives a summary of the models used in the Ensemble object
 #'
 #' @param object The Ensemble object to be summarized.
+#' @param ... Other arguments, if needed
+
 #'
 #' @return NULL, only prints out
 #'
@@ -64,6 +66,7 @@ summary.Ensemble <- function(object, ...) {
 #' @param voting.type The way that the Ensemble will vote - default is what was given
 #' at creation of the object but it can be overriden by passing in "averageVote", "majorityVote"
 #' or "majorityWeight."
+#' @param ... Other arguments, if needed
 #'
 #' @return a list of predictions, voted on by all the models into one final prediction.
 #'
@@ -123,7 +126,7 @@ predict.Ensemble <- function(object, newdata, voting.type="default", ...) {
 #'
 #' @examples
 #' # This function is used by predict.Ensemble. It's usage is as follows:
-#' MajorityVote(preds)
+#' # MajorityVote(preds)
 #'
 #' @keywords internal
 #' @export
@@ -161,7 +164,7 @@ MajorityVote <- function(list.of.predictions){
 #'
 #' @examples
 #' # This function is used by predict.Ensemble. It's usage is as follows:
-#' MajorityWeight(preds, Ensemble$weights)
+#' # MajorityWeight(preds, Ensemble$weights)
 #'
 #' @keywords internal
 #' @export
@@ -206,7 +209,7 @@ MajorityWeight <- function(list.of.predictions, weight.list){
 #'
 #' @examples
 #' # This function is used by predict.Ensemble. It's usage is as follows:
-#' AverageVote(preds)
+#' # AverageVote(preds)
 #'
 #' @keywords internal
 #' @export
@@ -249,7 +252,7 @@ AverageVote <- function(list.of.predictions){
 #'
 #' @examples
 #' # This function is used by GetWeightsFromTestSet It's usage is as follows:
-#' test.set <- GetFactorEqual(test.set)
+#' # test.set <- GetFactorEqual(test.set)
 #'
 #' @keywords internal
 #' @export
@@ -281,7 +284,7 @@ GetFactorEqual <- function(pred) {
 #'
 #' @examples
 #' # This function is used by Ensemble. It's usage is as follows:
-#' return(GetWeightsFromTestingSet(ensemble, weights, test.set, train.type))
+#' # return(GetWeightsFromTestingSet(ensemble, weights, test.set, train.type))
 #'
 #' @keywords internal
 #' @export
@@ -327,7 +330,7 @@ GetWeightsFromTestingSet <- function(ensemble, df.train, test.set, train.type) {
 #'
 #' @examples
 #' # This function is used by Ensemble. It's usage is as follows:
-#' ensemble$weight.list = GetModelWeights(ensemble, weights, test.set, train.type)
+#' # ensemble$weight.list = GetModelWeights(ensemble, weights, test.set, train.type)
 #'
 #' @keywords internal
 #' @export

diff --git a/R/ModelGeneration.R b/R/ModelGeneration.R
@@ -14,8 +14,8 @@
 #'
 #' @examples
 #' # This function is used by GetModelComparison and ModelComparison to create the
-#' ModelComparison object. The follow code is what is used by ModelComparison:
-#' CreateModelComparison(model.list, multi.class, F, names(model.list))
+#' # ModelComparison object. The follow code is what is used by ModelComparison:
+#' # CreateModelComparison(model.list, multi.class, F, names(model.list))
 #'
 #' @keywords internal
 #' @export
@@ -46,7 +46,7 @@ CreateModelComparison <- function(model.list, multi.class, force.prepped, diff.n
 #'
 #' @examples
 #' # see the CreateModelComparison function for it's use as follows:
-#'   comparison$accuracy.list <- GetAccuracy(comparison)
+#' #  comparison$accuracy.list <- GetAccuracy(comparison)
 #'
 #' @keywords internal
 #' @export
@@ -79,6 +79,7 @@ GetAccuracy <- function(object) {
 #'
 #' @param extra a boolean value on whether accuracy values will be returned, if present.
 #' By default this value is TRUE
+#' @param ... Other arguments, if needed
 #'
 #' @return NULL, only prints out
 #'
@@ -121,6 +122,7 @@ summary.ModelComparison <- function(object, extra=TRUE, ...) {
 #'
 #' @param object The ModelComparison object whose models will be predicted on.
 #' @param newdata A dataframe of new data that the models will use to predict.
+#' @param ... Other arguments, if needed
 #'
 #' @return A list of dataframes, where each dataframe is the predictions from the respective
 #'            model for the two output classes.
@@ -179,7 +181,7 @@ predict.ModelComparison <- function(object, newdata, ...) {
 #'
 #' @examples
 #' # This function is used by predict.ModelComparison. It's usage is as follows:
-#' pred.basic[[i]] = GetPredType(model, newdata)
+#' # pred.basic[[i]] = GetPredType(model, newdata)
 #'
 #' @keywords internal
 #' @export
@@ -213,7 +215,7 @@ GetPredType <- function(model, newdata) {
 #'
 #' @examples
 #' # This function is used by GetModelComparison. It's usage is as follows:
-#' training.set = prepData(training.set)
+#' # training.set = prepData(training.set)
 #'
 #' @keywords internal
 #' @export
@@ -250,8 +252,8 @@ prepData <- function(training.set) {
 #'
 #' @examples
 #' # This function is used by GetModelComparison. It's usage is as follows:
-#' modelVec = BuildModels(training.data, training.classes, trctrl,
-#' tune.length, multi.class, build.flags, force.prepared = forced.prepared)
+#' # modelVec = BuildModels(training.data, training.classes, trctrl,
+#' #            tune.length, multi.class, build.flags, force.prepared = forced.prepared)
 #'
 #' @keywords internal
 #' @export
@@ -360,7 +362,7 @@ BuildModels <- function(training.data, training.classes, trctrl,
 #'
 #' @examples
 #' # This function is used by GetModelComparison. It's usage is as follows:
-#' build.flags <- GetBuildFlags(model.list)
+#' # build.flags <- GetBuildFlags(model.list)
 #'
 #' @keywords internal
 #' @export
@@ -443,7 +445,7 @@ GetBuildFlags <- function(model.list) {
 #'
 #' @examples
 #' # This function is used by GetModelComparison. It's usage is as follows:
-#' training.info <- GetTrainingInfo(training.set, training.classes.input, validation, trctrl)
+#' # training.info <- GetTrainingInfo(training.set, training.classes.input, validation, trctrl)
 #'
 #' @keywords internal
 #' @export

diff --git a/R/Visualization.R b/R/Visualization.R
@@ -13,6 +13,8 @@
 #' @param format.data Whether the data should be transformed into one-hot encoding if it needs
 #' to be. The default is TRUE. If you would like to predict on unchanged data that is not
 #' in the right format, set this to false at your own risk.
+#' @param ... Other arguments for plotting
+
 #' @export
 #' @examples
 #' # prepare the dataset
@@ -96,7 +98,7 @@ plot.ModelComparison <- function(object, labels, training.data = "none", predict
 #'
 #' @examples
 #' # This function is used by plot.ModelComparison. It's usage is as follows:
-#'  CreateROCPlot(object, pred.basic, labels)
+#' # CreateROCPlot(object, pred.basic, labels)
 #' @keywords internal
 #' @export
 CreateROCPlot <- function(object, pred.basic, labels) {
@@ -141,9 +143,9 @@ CreateROCPlot <- function(object, pred.basic, labels) {
 #'
 #' @examples
 #' # This function is used by plot.ModelComparison. It's usage is as follows:
-#'  CreateCombinedPlot(object, pred.basic, labels)
-#'  # or given specific metrics for Accuracy and AUC:
-#'  CreateCombinedPlot(object, pred.basic, labels, c("Accuracy", "AUC"))
+#' #  CreateCombinedPlot(object, pred.basic, labels)
+#' # or given specific metrics for Accuracy and AUC:
+#' #  CreateCombinedPlot(object, pred.basic, labels, c("Accuracy", "AUC"))
 #' @keywords internal
 #' @export
 CreateCombinedPlot <- function(object, pred.basic, labels,
@@ -166,9 +168,9 @@ CreateCombinedPlot <- function(object, pred.basic, labels,
           dataScaled <- predict(preProcValues, ind.pred)
           # remove the matrix form
           ind.pred <- c(dataScaled)
-          value.list[[i]] = pROC:::auc(labels, ind.pred)[[1]]
+          value.list[[i]] = pROC::auc(labels, ind.pred)[[1]]
         } else {
-          value.list[[i]] = pROC:::auc(labels, ind.pred[, 1])[[1]]
+          value.list[[i]] = pROC::auc(labels, ind.pred[, 1])[[1]]
         }
       } else {
         if (names(pred.basic)[[i]] == "svm.formula") {
@@ -231,8 +233,8 @@ CreateCombinedPlot <- function(object, pred.basic, labels,
 #' @return The predictions, with only two factors.
 #'
 #' @examples
-#' As used in GetCombinedPlot:
-#' pred <- GetSVMScale(pred)
+#' # As used in GetCombinedPlot:
+#' # pred <- GetSVMScale(pred)
 #'
 #' @keywords internal
 #' @export

diff --git a/R/forRoxygen2.R b/R/forRoxygen2.R
diff --git a/man/AverageVote.Rd b/man/AverageVote.Rd
diff --git a/man/BuildModels.Rd b/man/BuildModels.Rd
diff --git a/man/CreateCombinedPlot.Rd b/man/CreateCombinedPlot.Rd
diff --git a/man/CreateModelComparison.Rd b/man/CreateModelComparison.Rd
diff --git a/man/CreateROCPlot.Rd b/man/CreateROCPlot.Rd
diff --git a/man/GetAccuracy.Rd b/man/GetAccuracy.Rd
diff --git a/man/GetBuildFlags.Rd b/man/GetBuildFlags.Rd
diff --git a/man/GetFactorEqual.Rd b/man/GetFactorEqual.Rd
diff --git a/man/GetModelWeights.Rd b/man/GetModelWeights.Rd
diff --git a/man/GetPredType.Rd b/man/GetPredType.Rd
diff --git a/man/GetSVMScale.Rd b/man/GetSVMScale.Rd
diff --git a/man/GetTrainingInfo.Rd b/man/GetTrainingInfo.Rd
diff --git a/man/GetWeightsFromTestingSet.Rd b/man/GetWeightsFromTestingSet.Rd
diff --git a/man/MajorityVote.Rd b/man/MajorityVote.Rd
diff --git a/man/MajorityWeight.Rd b/man/MajorityWeight.Rd
diff --git a/man/StripPredictions.Rd b/man/StripPredictions.Rd