论文信息 - An Improved Algorithm for Incremental Induction of Decision Trees

An Improved Algorithm for Incremental Induction of Decision Trees

This paper presents an algorithm for incremental induction of decision trees that is able to handle both numeric and symbolic variables. In order to handle numeric variables, a new tree revision operator called 'slewing' is introduced. Finally, a non-incremental method is given for finding a decision tree based on a direct metric of a candidate tree.

Paul E. Utgoff | P. Utgoff

[1] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .

[2] U. Fayyad. On the induction of decision trees for multiple concept learning , 1991 .

[3] Arthur L. Samuel,et al. Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..

[4] Paul E. Utgoff,et al. Improved Training Via Incremental Learning , 1989, ML.

[5] R. L. de Mantaras. A Distance-Based Attribute Selection Measure for Decision Tree Induction , 1991 .

[6] Patrick Henry Winston,et al. Learning structural descriptions from examples , 1970 .

[7] Allen Newell,et al. Chunking in Soar , 1986 .

[8] Tom Michael Mitchell. Version spaces: an approach to concept learning. , 1979 .

[9] Larry A. Rendell,et al. Lookahead Feature Construction for Learning Hard Concepts , 1993, International Conference on Machine Learning.

[10] Douglas H. Fisher,et al. A Case Study of Incremental Concept Induction , 1986, AAAI.