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» Ensembles of Multi-Objective Decision Trees
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WWW
2005
ACM
15 years 10 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han
JAIR
2008
93views more  JAIR 2008»
14 years 9 months ago
Spectrum of Variable-Random Trees
In this paper, we show that a continuous spectrum of randomisation exists, in which most existing tree randomisations are only operating around the two ends of the spectrum. That ...
Fei Tony Liu, Kai Ming Ting, Yang Yu, Zhi-Hua Zhou
KBSE
2000
IEEE
15 years 1 months ago
Practical Large Scale What-If Queries: Case Studies with Software Risk Assessment
When a lack of data inhibits decision making, large scale what-if queries can be conducted over the uncertain parameter ranges. Such what-if queries can generate an overwhelming a...
Tim Menzies, Erik Sinsel
JMLR
2008
116views more  JMLR 2008»
14 years 9 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
ML
2006
ACM
163views Machine Learning» more  ML 2006»
14 years 9 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel