Induction of Decision Trees

by: JR Quinlan

Mach. Learn., Vol. 1, No. 1. (March 1986), pp. 81-106.

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ACM, DOI, http://www.springerlink.com/content/q3018…

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Abstract

The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.

@article{citeulike:666326, abstract = {The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.}, address = {Hingham, MA, USA}, author = {Quinlan, J. R. }, citeulike-article-id = {666326}, doi = {10.1023/A:1022643204877}, issn = {0885-6125}, journal = {Mach. Learn.}, keywords = {cart, classification, machine-learning}, month = {March}, number = {1}, pages = {81--106}, posted-at = {2006-09-01 14:54:33}, priority = {2}, publisher = {Kluwer Academic Publishers}, title = {Induction of Decision Trees}, url = {http://portal.acm.org/citation.cfm?id=637969}, volume = {1}, year = {1986} }

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TY - JOUR ID - citeulike:666326 L3 - citeulike-article-id:666326 TI - Induction of Decision Trees JF - Mach. Learn. VL - 1 IS - 1 SP - 81 EP - 106 AD - Hingham, MA, USA PB - Kluwer Academic Publishers SN - 0885-6125 N2 - The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions. KW - cart KW - classification KW - machine-learning AU - Quinlan, JR PY - 1986/03// UR - http://portal.acm.org/citation.cfm?id=637969 ER -

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