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» DIVACE: Diverse and Accurate Ensemble Learning Algorithm
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ICIC
2007
Springer
14 years 1 months ago
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal...
Huanhuan Chen, Xin Yao
NAACL
2010
13 years 4 months ago
Ensemble Models for Dependency Parsing: Cheap and Good?
Previous work on dependency parsing used various kinds of combination models but a systematic analysis and comparison of these approaches is lacking. In this paper we implemented ...
Mihai Surdeanu, Christopher D. Manning
ECAI
2008
Springer
13 years 8 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
IDA
2007
Springer
14 years 1 months ago
Two Bagging Algorithms with Coupled Learners to Encourage Diversity
In this paper, we present two ensemble learning algorithms which make use of boostrapping and out-of-bag estimation in an attempt to inherit the robustness of bagging to overfitti...
Carlos Valle, Ricardo Ñanculef, Héct...
ESANN
2006
13 years 8 months ago
Diversity creation in local search for the evolution of neural network ensembles
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mec...
Pete Duell, Iris Fermin, Xin Yao