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**3)** Produce the category normalization weights for the training sample with **Normalization_Weights.C** and save the output to a text such as // | **3)** Produce the category normalization weights for the training sample with **Normalization_Weights.C** and save the output to a text such as // | ||
- | **4)** Assuming the evaluation sample vertex category weights have been produced (look at procedures for Evaluation Samples), add the normalization and category weight branches to the flat ntuples with **addWeightBranch.py**. The combination of these weights will remove the training sample vertex category information and match it with that of the evaluation sample. | + | **4)** Assuming the evaluation sample vertex category weights have been produced (look at procedures for Evaluation Samples, step 3), add the normalization and category weight branches to the flat ntuples with **addWeightBranch.py**. The combination of these weights will remove the training sample vertex category information and match it with that of the evaluation sample. |
**5)** Create 2D Pt/Eta Histograms for the weighted ntuples with **createEtaPtWeightHists.py** (make sure " | **5)** Create 2D Pt/Eta Histograms for the weighted ntuples with **createEtaPtWeightHists.py** (make sure " |