论文信息 - Relationships Between Average Depth and Number of Nodes for Decision Trees

Relationships Between Average Depth and Number of Nodes for Decision Trees

This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1].

[1] Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[2] Andrzej Skowron,et al. The Discernibility Matrices and Functions in Information Systems , 1992, Intelligent Decision Support.

[3] Hung Son Nguyen,et al. From Optimal Hyperplanes to Optimal Decision Trees , 1998, Fundam. Informaticae.

[4] Igor Chikalov,et al. A Tool for Study of Optimal Decision Trees , 2010, RSKT.

[5] Igor Chikalov,et al. On Algorithm for Building of Optimal alpha-Decision Trees , 2010, RSCTC.

[6] Shahid Hussain,et al. Dagger: A Tool for Analysis and Optimization of Decision Trees and Rules , 2011 .

[7] Shahid Hussain,et al. Extensions of Dynamic Programming as a New Tool for Decision Tree Optimization , 2013 .