check data spliting for cal_feature_sel in trans_classifier

R/trans_classifier.R

@@ -185,6 +185,8 @@ trans_classifier <- R6::R6Class(classname = "trans_classifier",
 			boruta.repetitions = 4,
 			...
 			){
+			self <- private$check_training_data(self)
+
 			data_input <- self$data_train
 			data_x <- data_input[, -1]
 			data_y <- data_input[, 1]
@@ -215,11 +217,14 @@ trans_classifier <- R6::R6Class(classname = "trans_classifier",
 			data_output <- data_input[, c(colnames(data_input)[1], boruta.list.top)]
 			self$data_train <- data_output
 
-			data_input <- self$data_test
-			data_output <- data_input[, c(colnames(data_input)[1], boruta.list.top)]
-			self$data_test <- data_output
-
-			message("Selected features are reassigned to object$data_train and object$data_test ...")
+			if(is.null(self$data_test)){
+				message("Selected features are reassigned to object$data_train ...")
+			}else{
+				data_input <- self$data_test
+				data_output <- data_input[, c(colnames(data_input)[1], boruta.list.top)]
+				self$data_test <- data_output
+				message("Selected features are reassigned to object$data_train and object$data_test ...")
+			}
 			invisible(self)
 		},
 		#' @description
@@ -279,15 +284,9 @@ trans_classifier <- R6::R6Class(classname = "trans_classifier",
 			ntree = 500,
 			...
 			){
+			self <- private$check_training_data(self)
 			train_data <- self$data_train
-			if(is.null(train_data)){
-				message("No training data is found! The reason is function cal_split is not performed! Use all the samples for the training ...")
-				train_data <- data.frame(Response = self$data_response, self$data_feature, check.names = FALSE)
-				if(self$type == "Classification"){
-					train_data$Response %<>% as.factor
-				}
-				self$data_train <- train_data
-			}
+
 			trControl <- self$trainControl
 			if(is.null(trControl)){
 				trControl <- caret::trainControl()
@@ -775,6 +774,20 @@ trans_classifier <- R6::R6Class(classname = "trans_classifier",
 			p
 		}
 	),
+	private = list(
+		check_training_data = function(self){
+			train_data <- self$data_train
+			if(is.null(train_data)){
+				message("No training data is found! The reason is that the cal_split function is not performed! Use all the samples for the training ...")
+				train_data <- data.frame(Response = self$data_response, self$data_feature, check.names = FALSE)
+				if(self$type == "Classification"){
+					train_data$Response %<>% as.factor
+				}
+				self$data_train <- train_data
+			}
+			self
+		}
+	),
 	lock_class = FALSE,
 	lock_objects = FALSE
 )