First, read the root file and convert it into the format you want (csv, root etc)
Second, proceed with standard steps of reading the columns, divide into X (features) and Y (dependent variable).
Third, split the data into training and test data sets.
Fourth, edit your own code to calculate prediction, confusion matrix and accuracy for D0-meson.
You can check the function "pred_score" defined in https://github.com/sparmar24/machine_learning/blob/main/src/modelvalidation_casestudy.py#L44 It will calculate prediction, confusion matrix and accuracy.
Further, in the main function, https://github.com/sparmar24/machine_learning/blob/main/src/modelvalidation_casestudy.py#L53
A dictionary named "models_and_predictions" is created.
A full code is available at address, https://github.com/sparmar24/machine_learning/blob/main/src/modelvalidation_casestudy.py
First, read the root file and convert it into the format you want (csv, root etc) Second, proceed with standard steps of reading the columns, divide into X (features) and Y (dependent variable). Third, split the data into training and test data sets. Fourth, edit your own code to calculate prediction, confusion matrix and accuracy for D0-meson.