Open AccessA Review of Decision Tree Classification Algorithms for Continuous Variables
Author(s) -
S R Jiao,
Jie Song,
B Liu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012083
Subject(s) - decision tree , incremental decision tree , computer science , cart , decision tree learning , tree (set theory) , division (mathematics) , algorithm , id3 algorithm , data mining , machine learning , artificial intelligence , mathematics , engineering , arithmetic , mechanical engineering , mathematical analysis
Improving the division accuracy and efficiency of continuous variables has always been an important direction of decision tree research. This article briefly introduces the development of decision tree, focuses on the two types of decision tree algorithms for non-traditional continuous variables — based on CART and based on statistical models. Finally, the future development trend of decision tree algorithms for continuous variables is discussed.