Abstract
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.
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CITATION STYLE
Jiao, S. R., Song, J., & Liu, B. (2020). A Review of Decision Tree Classification Algorithms for Continuous Variables. In Journal of Physics: Conference Series (Vol. 1651). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1651/1/012083
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