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јвтор:  Goubko M. V.
Ќазвание:  Lower-bound Estimate for Cost-sensitive Decision Trees
—татус:  опубликовано
√од:  2011
“ип публикации:  доклад
ѕолна€ библиографическа€ ссылка:  Goubko M.V. Lower-bound Estimate for Cost-sensitive Decision Trees // Preprints of the 18th IFAC World Congress, Milano (Italy), August 28 - September 2, 2011. P. 9005-9010.
јннотаци€:  While an extensive body of literature investigates problems of decision trees growing, just a few study lower-bound estimates for the expected classification cost of decision trees, especially for varying costs of tests. In this paper a new lower-bound estimate is proposed. Computation of the estimate is reduced to solving a series of set-covering problems. Computational complexity and other properties of the lower-bound estimate are investigated. The top-down algorithm of tree construction based on the proposed estimate is tested against several popular greedy cost-sensitive heuristics on a range of standard data sets from UCI Machine Learning Repository.
–асширени€ базовой модели:  —ообщение информации
ћетод моделировани€:  ƒискретна€ математика
ѕредметные области и задачи управлени€:  ѕрин€тие решений

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