A novel approach to build accurate and diverse decision tree forest-Reference-Cited by-同舟云学术

A novel approach to build accurate and diverse decision tree forest

Published:2021-01-03 Issue: Volume: Page:
ISSN:1864-5909
Container-title:Evolutionary Intelligence
language:en
Short-container-title:Evol. Intel.

Author:

Panhalkar Archana R.^ORCID,Doye Dharmpal D.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s12065-020-00519-0.pdf

Reference42 articles.

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3. Kuncheva LI (2005) Using diversity measures for generating error-correcting output codes in classifier ensembles. Pattern Recogn Lett 26(1):83–90

4. Shipp CA, Kuncheva LI (2002) Relationships between combination methods and measures of diversity in combining classifiers. Inform Fusion 3:135–148

5. Dua D, Graff C (2019) UCI machine learning repository. School of Information and Computer Science, University of California, Irvine, CA. http://archive.ics.uci.edu/ml

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