diff --git a/demo/regression/README.md b/demo/regression/README.md
index 2002f5bac..7b8b8cbe0 100644
--- a/demo/regression/README.md
+++ b/demo/regression/README.md
@@ -6,7 +6,7 @@ Using XGBoost for regression is very similar to using it for binary classificati
 The dataset we used is the [computer hardware dataset from UCI repository](https://archive.ics.uci.edu/ml/datasets/Computer+Hardware). The demo for regression is almost the same as the [binary classification demo](../binary_classification), except a little difference in general parameter:
 ```
 # General parameter
-# this is the only difference with classification, use reg:linear to do linear classification
+# this is the only difference with classification, use reg:linear to do linear regression
 # when labels are in [0,1] we can also use reg:logistic
 objective = reg:linear
 ...