Review-home.md

@@ -6,7 +6,7 @@ Review work can be divided into three portion (in branch random)
 3. Implementation in em_bright.py
 
 ### Random forest implementation
-Relevant lines : [random forest](https://git.ligo.org/sushant.sharma-chaudhary/em-bright-rf/-/blob/random/ligo/em_bright/utils.py#L286-312)
+Relevant lines : [random forest](https://git.ligo.org/sushant.sharma-chaudhary/em-bright-rf/-/blob/random/ligo/em_bright/utils.py#L322-364)
 
 It takes the dataset form Deep's KNN framework, split them to train test (70% training and 30% testing), and then training set is passed onto RandomForest classifier. The **kwargs for the classifier is taken from the config file (./etc/config).