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ECML
2007
Springer
15 years 3 months ago
Ensembles of Multi-Objective Decision Trees
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...
ICML
2010
IEEE
15 years 10 days ago
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
Seyoung Kim, Eric P. Xing
ML
2006
ACM
163views Machine Learning» more  ML 2006»
14 years 11 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
BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
14 years 8 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
ICMLA
2007
15 years 21 days ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis