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» A streaming ensemble algorithm (SEA) for large-scale classif...
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KDD
2001
ACM
152views Data Mining» more  KDD 2001»
16 years 23 hour ago
A streaming ensemble algorithm (SEA) for large-scale classification
W. Nick Street, YongSeog Kim
80
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LREC
2010
206views Education» more  LREC 2010»
15 years 1 months ago
Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain
In this paper we evaluate the performance of multilabel classification algorithms on the EUR-Lex database of legal documents of the European Union. On the same set of underlying d...
Eneldo Loza Mencía, Johannes Fürnkranz
117
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TNN
2010
176views Management» more  TNN 2010»
14 years 6 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
108
Voted
DCAI
2008
15 years 1 months ago
Solving the Oil Spill Problem Using a Combination of CBR and a Summarization of SOM Ensembles
. In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodolo...
Aitor Mata, Emilio Corchado, Bruno Baruque
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
15 years 6 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof