Remember to overwrite preloaded data

+otherwise we forget to filter NA's

Author: koenderks

R/commonMachineLearningClassification.R

@@ -42,9 +42,7 @@
 }
 
 .mlClassificationReadData <- function(dataset, options) {
-  if (is.null(dataset)) {
-    dataset <- .readDataClassificationRegressionAnalyses(dataset, options)
-  }
+  dataset <- .readDataClassificationRegressionAnalyses(dataset, options)
   if (length(unlist(options[["predictors"]])) > 0 && options[["scaleVariables"]]) {
     dataset[, options[["predictors"]]] <- .scaleNumericData(dataset[, options[["predictors"]], drop = FALSE])
   }

R/commonMachineLearningClustering.R

@@ -33,9 +33,7 @@
 .mlClusteringReadData <- function(dataset, options) {
   predictors <- unlist(options[["predictors"]])
   predictors <- predictors[predictors != ""]
-  if (is.null(dataset)) {
-    dataset <- .readAndAddCompleteRowIndices(options, "predictors")
-  }
+  dataset <- .readAndAddCompleteRowIndices(options, "predictors")
   if (options[["scaleVariables"]] && length(unlist(options[["predictors"]])) > 0) {
     dataset <- .scaleNumericData(dataset)
   }

R/commonMachineLearningRegression.R

@@ -45,9 +45,7 @@
 }
 
 .readDataRegressionAnalyses <- function(dataset, options, jaspResults) {
-  if (is.null(dataset)) {
-    dataset <- .readDataClassificationRegressionAnalyses(dataset, options)
-  }
+  dataset <- .readDataClassificationRegressionAnalyses(dataset, options)
   if (length(unlist(options[["predictors"]])) > 0 && options[["scaleVariables"]]) {
     dataset[, options[["predictors"]]] <- .scaleNumericData(dataset[, options[["predictors"]], drop = FALSE])
   }
@@ -72,9 +70,7 @@
         options[[name2]] <- rep("scale", length(options[[name]]))
     }
   dataset <- jaspBase::readDataSetByVariableTypes(options, c(optionNames, optionNamesAsNumeric))
-  complete.index <- which(complete.cases(dataset))
-  dataset <- na.omit(dataset)
-  rownames(dataset) <- as.character(complete.index)
+  dataset <- jaspBase::excludeNaListwise(dataset, c(options[["target"]], options[["predictors"]]))
   return(dataset)
 }
 

R/mlRegressionRegularized.R

@@ -74,9 +74,7 @@ mlRegressionRegularized <- function(jaspResults, dataset, options, ...) {
 
   predictors <- unlist(options["predictors"])
   predictors <- predictors[predictors != ""]
-  if (is.null(dataset)) {
-    dataset <- .readAndAddCompleteRowIndices(options, c("target", "predictors", "weights"), testSetIndicator)
-  }
+  dataset <- .readAndAddCompleteRowIndices(options, c("target", "predictors", "weights"), testSetIndicator)
   if (length(unlist(options[["predictors"]])) > 0 && options[["scaleVariables"]]) {
     dataset[, options[["predictors"]]] <- .scaleNumericData(dataset[, options[["predictors"]], drop = FALSE])
   }