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The processes are characterized by the same final-state particles but we can use the value of multiple variables, such as kinematic properties of the particles, for classifying data into the two categories, signal, and background. The first one is the statistically less probable process that results in producing the Higgs boson at the Large Hadron Collider (LHC) experiments and it is still understudies by the CMS collaboration.
In order to train our Machine Learning algorithms, we will look at the decay products of our physics problem. In our case we going to deal with:
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