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» Design Pattern Mining Enhanced by Machine Learning
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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 8 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
ICDM
2006
IEEE
182views Data Mining» more  ICDM 2006»
14 years 1 months ago
Active Learning to Maximize Area Under the ROC Curve
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Matt Culver, Kun Deng, Stephen D. Scott
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 8 months ago
Using retrieval measures to assess similarity in mining dynamic web clickstreams
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
Olfa Nasraoui, Cesar Cardona, Carlos Rojas
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
13 years 11 months ago
Sets of receiver operating characteristic curves and their use in the evaluation of multi-class classification
Within the last two decades, Receiver Operating Characteristic (ROC) Curves have become a standard tool for the analysis and comparison of classifiers since they provide a conveni...
Stephan M. Winkler, Michael Affenzeller, Stefan Wa...
ECML
2007
Springer
14 years 2 months ago
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...
Rikiya Takahashi