On learning decision trees with large output domains (extended abstract)

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On learning decision trees with large output domains (extended abstract)

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Annual Workshop on Computational Learning Theory archive
Proceedings of the eighth annual conference on Computational learning theory table of contents

Santa Cruz, California, United States

Pages: 190 - 197

Year of Publication: 1995

ISBN:0-89791-723-5

Authors

Nader H. Bshouty	Department of Computer Science, The University of Calgary, Calgary, Alberta, Canada T2N 1N4
Christino Tamon	Department of Computer Science, The University of Calgary, Calgary, Alberta, Canada T2N 1N4
David K. Wilson	Department of Computer Science, The University of Calgary, Calgary, Alberta, Canada T2N 1N4

Sponsors

SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
University of California : University of California

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 13, Downloads (12 Months): 23, Citation Count: 1

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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