--- a
+++ b/bin/normalization.r
@@ -0,0 +1,90 @@
+# install.packages("class")
+# install.packages("gmodels")
+
+# function that normalizes
+normalize <- function(x) {
+  return ((x - min(x)) / (max(x) - min(x))) 
+}
+  
+
+# function that converts a string 
+# https://stats.stackexchange.com/a/17995
+fromStringToNumeric <- function(x_array) {
+
+   new_x <- as.factor(x_array)
+   levels(new_x) <- 1:length(levels(new_x))
+   new_x_num <- as.numeric(new_x)
+
+   return (new_x_num)
+}
+
+
+cat("[Reading the data file]\n")
+lung_cancer_data <- read.csv("../data/LungCancerDataset_AllRecords.csv", stringsAsFactors = FALSE) 
+
+
+num_of_columns_original <- dim(lung_cancer_data)[2]
+num_of_instances <- dim(lung_cancer_data)[1]
+num_of_features_original <- num_of_columns_original - 1
+
+lung_cancer_data_original <- lung_cancer_data
+
+lung_cancer_data$Metastasis <- lung_cancer_data$M
+lung_cancer_data$M <- NULL
+
+
+print("M0 = 0 = tumor NOT spread to distant organs")
+print("M1 = 1 = tumor spread to distant organs")
+
+table(lung_cancer_data$Metastasis)  # it helps us to get the numbers of patients
+lung_cancer_data$Metastasis <- factor(lung_cancer_data$Metastasis, levels = c("M0", "M1"), labels = c("0", "1"))
+
+lung_cancer_data$Metastasis <- as.numeric(lung_cancer_data$Metastasis)-1
+
+colnames(lung_cancer_data)
+
+lung_cancer_data_num <- lung_cancer_data
+
+# Le's remove this feature that has only one value
+#lung_cancer_data$SiterecwithKaposiandmesothelioma <- NULL 
+
+j = 1
+for(i in 1:(num_of_columns_original))
+{
+  if (table(lung_cancer_data[i])==num_of_instances) {
+  
+    cat("The column ", colnames(lung_cancer_data[i]), "[",i,"] has only one value so will be deleted\n");
+    lung_cancer_data_num[j] <- NULL
+    j = j - 1
+  }
+  j = j + 1
+}
+
+lung_cancer_data_num$Stage <- NULL
+
+num_of_columns <- dim(lung_cancer_data_num)[2]
+num_of_features <- num_of_columns - 1
+
+target_column_index <- grep("Metastasis", colnames(lung_cancer_data_num))
+
+cat("num_of_features = ", num_of_features, "\n")
+cat("the target is lung_cancer_data_num$Metastasis, column index =", target_column_index, "\n")
+
+for(i in 1:(num_of_features))
+{
+  lung_cancer_data_num[,i] <- fromStringToNumeric(lung_cancer_data_num[,i])
+}
+lung_cancer_data_num$Metastasis <- lung_cancer_data$Metastasis
+# lung_cancer_data_num <- lung_cancer_data_num[sample(nrow(lung_cancer_data_num)),] # shuffle the rows
+
+
+round(prop.table(table(lung_cancer_data_num$Metastasis)) * 100, digits = 1)  # it gives the result in the percentage form rounded of to 1 decimal place( and so it’s digits = 1)
+
+cat("[Normalizing the values of the data file (except the Metastasis target column)]\n")
+lung_cancer_data_norm <- as.data.frame(lapply(lung_cancer_data_num[1:num_of_features], normalize))
+lung_cancer_data_norm$Metastasis <- lung_cancer_data_num$Metastasis
+
+colnames(lung_cancer_data_norm)
+
+write.table(lung_cancer_data_norm, file = "../data/LungCancerDataset_AllRecords_NORM.csv", row.names=FALSE, na="", col.names=TRUE, sep=",")
+