Optimization of team selection in fantasy cricket: a hybrid approach using recursive feature elimination and genetic algorithm

DOI10.1007/S10479-022-04726-ZOpenAlexW4280566402MaRDI QIDQ6170886

Arpan Kumar Kar, Apurva Jha, Agam Gupta

Publication date: 13 July 2023

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-022-04726-z

zbMATH Keywords

genetic algorithmmachine learningteam selectionrandom forestfantasy sports

Mathematics Subject Classification ID

Mathematical programming (90Cxx) Applications of statistics (62Pxx) Operations research and management science (90Bxx)

Cites Work

• Unnamed Item
• A network DEA assessment of team efficiency in the NBA
• Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA
• An objective approach of balanced cricket team selection using binary integer programming method
• The sport teams grouping problem
• An analytics approach to the FIFA ranking procedure and the World Cup final draw
• A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics
• A criterion for comparing and selecting batsmen in limited overs cricket
• 10.1162/153244303322753616
• Towards fairer measures of player performance in one-day cricket
• Gene selection for cancer classification using support vector machines

This page was built for publication: Optimization of team selection in fantasy cricket: a hybrid approach using recursive feature elimination and genetic algorithm