Review-home.md

+# EM-Bright random forest review
+## Outlook of the code
+Review work can be divided into three portion
+1. Random forest implementation
+2. Condor dag writer script
+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)
+
+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).
+
+### Condor dag writer script
+Script : [Dag Writer](https://git.ligo.org/sushant.sharma-chaudhary/em-bright-rf/-/blob/random/ligo/em_bright/dag_writer.py)
+
+This code writes the workflow dag in order to submit to condor. It again take's Deep's common workflow scheme and separates for KNN and RandomForest classifier.
+
+### Implementation in em_bright.py