Soukaina Mjahed1,*, Khadija Bouzaachane1, Ahmad Taher Azar2,3, Salah El Hadaj1, Said Raghay1
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 459-494, 2020, DOI:10.32604/cmes.2020.010791
Abstract This paper focuses on the unsupervised detection of the Higgs boson
particle using the most informative features and variables which characterize
the “Higgs machine learning challenge 2014” data set. This unsupervised
detection goes in this paper analysis through 4 steps: (1) selection of the most
informative features from the considered data; (2) definition of the number of
clusters based on the elbow criterion. The experimental results showed that
the optimal number of clusters that group the considered data in an unsupervised manner corresponds to 2 clusters; (3) proposition of a new approach
for hybridization of both hard and fuzzy clustering… More >
Login
Register
