first commit

+df<-read.csv('result_4.csv')
+tail(df,10)
+set.seed(2)
+id<-sample(2,nrow(df),prob = c(0.8,0.2), replace = TRUE)
+train<-df[id==1,]
+test<-df[id==2,]
+tail(test,2)
+
+library(C50)
+model <- readRDS("./c5_model.rds")
+
+prob <- predict(model, newdata = test[1:1, 1:126], type = "prob")
+max1 <- 0
+max2 <- 0
+max3 <- 0
+idx1 <- -1
+idx2 <- -1
+idx3 <- -1
+
+for(i in 1:17){
+  if(max1 < prob[1:1,i:i]){
+    max3 <- max2
+    max2 <- max1
+    max1 <- prob[1:1,i:i]
+    idx3 <- idx2
+    idx2 <- idx1
+    idx1 <- i
+  }
+  else{
+    if(max2 <prob[1:1,i:i]){
+      max3 <- max2
+      max2 <- prob[1:1,i:i]
+      idx3 <- idx2
+      idx2 <- i
+    }
+    else{
+      if(max3 <prob[1:1,i:i]){
+        max3 <-prob[1:1,i:i]
+        idx3 <-i
+      }
+    }
+  }
+}
+
+library(ggplot2)
+v <-c("51","54,51","56","56,51","56,54,51","59","59,51","59,56,51","59,56,54,51",
+      "61,51","61,54,51","61,56,51","61,56,54,51","61,59,51","61,59,54,51",
+      "61,59,56,51","61,59,56,54,51")
+plot <- list(data.frame(idx=toString(v[idx1]),probability=max1),data.frame(idx=toString(v[idx2]),probability=max2),data.frame(idx=toString(v[idx3]),probability=max3))
+newplot <- do.call(rbind,plot)
+p <- ggplot(newplot,aes(idx,probability))+geom_bar(stat="identity",fill = "blue")
+ggsave(file="~/bar_plot.png",plot=p,dpi=300)