PREDICTION OF DECAY MODES OF HIGGS BOSON USING CLASSIFICATION ALGORITHMS
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Computational algorithms have been implied to various problems in particle physics from the explosion of applications in particles to event identification and reconstruction. The motive of this study is to propose a model that predicts the decay events of High Boson as “tau-tau decay of High Boson” or" the background noise" after applying some feature extraction on the CERN dataset. Therefore, eight algorithms namely “K” Nearest Neighbor, Artificial Neural Networks, Naïve Bayes algorithm, Logistic Regression algorithm, SVM, Random Forest Decision Tree, and Gradient Boosting are used in this experiment. The performances of all the algorithms are examined basis accuracy and computational time. Derived results show the decision tree outperforms the best on measures like Accuracy and Computational Time.
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