Adds reproducible script for the article

Author: ncordon

R/imbalance.R

@@ -24,6 +24,7 @@ NULL
 
 #' @useDynLib imbalance, .registration = TRUE
 #' @importFrom Rcpp sourceCpp
+#' @import smotefamily
 NULL
 
 
@@ -48,7 +49,6 @@ NULL
 #'
 #' @return A balanced \code{data.frame} with same structure as \code{dataset},
 #'   containing both original instances and new ones
-#' @import smotefamily
 #' @export
 #'
 #' @examples

data-raw/banana.R

@@ -0,0 +1,66 @@
+library("imbalance")
+library("ggplot2")
+library("caret")
+set.seed(12345)
+
+# Load original banana dataset
+data(banana_orig)
+# Load imbalanced banana dataset
+data(banana)
+# Limits for the plot axis
+myxlim <- c(-4, 4)
+myylim <- c(-3, 4)
+# Methods to apply and plot
+methods <- c("original", "imbalanced", "SMOTE", "MWMOTE", "RWO", "PDFOS")
+
+for(i in seq_along(methods)){
+  method <- methods[i]
+
+  if(method == "original"){
+    dataset <- banana_orig
+  }else{
+    if(method == "imbalanced"){
+      dataset <- banana
+    }else{
+      dataset <- oversample(banana, ratio = 0.7, method = method, filtering = T)
+    }
+
+    model <- knn3Train(dataset[, -3], banana_orig[, -3], dataset$Class, k = 3, l = 0, prob = TRUE, use.all = TRUE)
+    model[model == "negative"] <- -1
+    model[model == "positive"] <- 1
+    model <- as.numeric(model)
+    modelauc <- auc(banana_orig[, 3], model)
+    print(paste(method, "AUC:", modelauc))
+  }
+
+  qplot(At1, At2, col = Class, data = dataset,
+        xlab = "at1", ylab = "at2", xlim = myxlim, ylim = myylim) +
+        scale_colour_manual(values = c("#E69F00", "#000000")) +
+        geom_point(size = 2, alpha = 0.3) +
+        theme(text = element_text(size = 30), legend.position="none")
+
+  ggplot(dataset, aes_string("At1", "At2", col = "Class")) +
+    geom_point(alpha = 0.3) +
+    scale_color_manual(values = c("#E69F00", "#000000")) +
+    geom_point(size = 3, alpha = 0.3) +
+    theme(text = element_text(size = 30), legend.position="none")
+
+        # theme(axis.text.x = element_text(size = 15),
+        #   axis.text.y = element_text(size = 15),
+        #   axis.title.x = element_text(size = 20),
+        #   axis.title.y = element_text(size = 20))
+  ggsave(paste("banana-", method, ".png", sep = ""), device = "png", width = 14, height = 7.85)
+}
+
+
+# 3-repeated 3-fold cross validation
+# control <- trainControl(method = "repeatedcv", number = 3, repeats = 3,
+#                         summaryFunction = twoClassSummary, classProbs = TRUE)
+#
+# model <- train(Class~., data = dataset, method="kknn",
+#                trControl=control,
+#                metric = "ROC",
+#                tuneGrid = data.frame(kmax = 5, distance = 2, kernel = "rectangular"))
+# model$results
+
+