diff --git a/Solutions to the questions concerning R language.md b/Solutions to the questions concerning R language.md
index e09b9f4..b240d01 100644
--- a/Solutions to the questions concerning R language.md	
+++ b/Solutions to the questions concerning R language.md	
@@ -378,8 +378,7 @@ summary(tune.out)
 ## 2   0.01778 0.3675    0.05076
 ## 3   0.03162 0.3575    0.05177
 ## 4   0.05623 0.3425    0.04937
-## 5   0.10000 0.3150    0.05231
-## 6   0.17783 0.2487    0.03929
+****## 6   0.17783 0.2487    0.03929
 ## 7   0.31623 0.2088    0.05684
 ## 8   0.56234 0.2088    0.05653
 ## 9   1.00000 0.2000    0.06095
@@ -421,4 +420,7 @@ table(OJ.test$Purchase, test.pred)
 ```
 ## [1] 0.1741
 ```
+Tuning reduces the training error to 15.12% and test error to 17.4% which is worse than radial kernel but slightly better than linear kernel.
 
+**viii.**
+Overall, radial basis kernel seems to be producing minimum misclassification error on both train and test data.