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README.md

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-# hh2yybbEventClassifier
+# hh2yybb Event Classifier
 Event level classifier for the hh-->yybb analysis using multi-stream RNNs
+
+## Project Title: Develop a ML algorithm to distinguish SM hh (gamma-gamma bb) events from background 
+
+### Purpose: 
+ATLAS has a ‘cut based’ hh data analysis. To improve on this, a ML algoorithm is being trained to select the correct “second b jet” in single-tagged events ([bbyy jet classifier](https://github.com/jemrobinson/bbyy_jet_classifier)). The project proposed here will take this a step further and develop an algorithm for all events passing some minimum selection criteria, not just single-tagged events. 
+
+### To-do list:
+
+* Produce the ntuples using `HGamAnalysisFramework`:  
+     Decide what info to include (jets and photons, but also leptons, pileup info?)   
+     Apply the pre-selection </br>
+     Assign truth labels using b-quark-from-Higgs labeling scheme </br>
+     Actually make the ntuples on grid – run on signal and bkg events
+
+* Analysis Coding Tasks -- Modules needed: 
+   1. Read-in module that knows about the ntuple format 
+   2. Data processing module that uses `scikit-learn` to: </br>
+      scale all variables to have mean zero and sd of 1 </br>
+      shuffle events  </br>
+      split data into training and testing samples 
+   3. Plotting module to check all variables before training, both scaled and pre-scaled variables to make sure things look reasonable and there are no bugs 
+   4. Training module that uses `Keras` (design RNN, test different NN architectures, etc.) 
+   5. Testing module to check performance and produce ROC curves. Plot ROC curve as a function of mu (pile-up), pt of largest jet, Njets, etc. 
+
+* Write presentations
+
+---
+This project has been assigned to [@gstark12](https://github.com/gstark12) and [@jennyailin](https://github.com/jennyailin) as part of their Summer 2016 internship at CERN. They will work under the supervision of [@mickypaganini](https://github.com/mickypaganini) and Prof. Paul Tipton.