For a multi-class problem, this paper proposes to induce individually the 1-vs-others rough decision trees for all classes, and finally construct a rough ...
Page 1. 1-vs-Others Rough Decision Forest. Jinmao Wei1, Shuqin Wang2 ... inducing the 1-vs-others decision trees for all classes, the rough decision forest.
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Oct 1, 2010 · For a multi-class problem, this paper proposes to induce individually the 1-vs-others rough decision trees for all classes, and finally ...
The procedure runs in one pass and is very fast. Other than minor difficulties caused by the size of the search steps or identical samples, it always stops when.
Jan 15, 2020 · Random Forest does not use this method, as it actually takes advantage of the high variance of the overfitted decision trees by averaging them.
Oct 17, 2019 · Majority voting, which is also called Hard Voting, every individual classifier votes for a class, and the majority wins.
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1-vs-others rough decision forest. RSKT'10: Proceedings of the 5th international conference on Rough set and knowledge technology. Bootstrap, boosting and ...
Nov 22, 2011 · Compared to a single decision tree, or to a set of rules, they don't give you a lot of insight. They are hard to make incremental. It can be ...
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Zhou et al. Selective ensemble of decision trees · Rough sets, fuzzy sets, data mining, and granular computing. (2003). R.C. Fong et al. Interpretable ...
When would you prefer decision tree over random forest? - Quora
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Sep 28, 2018 · They are typically more accurate than single decision trees. The decision boundary becomes more accurate and stable as more trees are added.