Open AccessPerformance analysis of set partitioning formulations on the rule extraction from random forests
Author(s) -
Mert Edali
Publication year - 2021
Publication title -
mühendislik bilimleri dergisi/mühendislik bilimleri dergisi
Language(s) - English
Resource type - Journals
eISSN - 2147-5881
pISSN - 1300-7009
DOI - 10.5505/pajes.2020.05926
Subject(s) - extraction (chemistry) , computer science , random forest , set (abstract data type) , data mining , artificial intelligence , chromatography , chemistry , programming language