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PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
AAMAS
2012
Springer
12 years 1 months ago
Winner determination in voting trees with incomplete preferences and weighted votes
In multiagent settings where agents have different preferences, preference aggregation can be an important issue. Voting is a general method to aggregate preferences. We consider ...
Jérôme Lang, Maria Silvia Pini, Franc...
ECML
2004
Springer
13 years 10 months ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
ICMLA
2007
13 years 6 months ago
Estimating class probabilities in random forests
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
Henrik Boström
NAACL
2010
13 years 3 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