Use of Machine Learning Technique to maximize the signal over background for H → ττ
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In recent years, artificial neural networks (ANNs) have won numerous contests in pattern recognition and machine learning. ANNS have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers, and gene prediction. Here, we intend to maximize the chances of finding the Higgs boson decays to two τ leptons in the pseudo dataset using a Machine Learning technique to classify the recorded events as signal or background.
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