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Learning Goals
- You will learn how a multivariate analysis Multivariate Analysis algorithm works (see the below introduction) and more specifically how a Machine Learning model must be implemented;
- you will acquire basic knowledge about the Higgs boson physics as described by the Standard Model. During the exercise you will be invited to plot some physical quantities in order to understand what is the underlying Particle Physics problem;
- you will be invited to change hyperparameters of the ANN and the RF algorithms to understand better what are the consequences in terms of the models' performances;
- you will understand that the choice of the input variables is the key to the goodness of the algorithm since an optimal choice allows achieving the best possible performances;
- moreover, you will have the possibility of changing the background datasets, the decay channels of the final state particles, and seeing how the ML algorithms' performance changes.
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