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» Learning decision trees from dynamic data streams
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JMLR
2010
130views more  JMLR 2010»
13 years 2 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
FGCS
2007
99views more  FGCS 2007»
13 years 7 months ago
Mining performance data for metascheduling decision support in the Grid
: Metaschedulers in the Grid needs dynamic information to support their scheduling decisions. Job response time on computing resources, for instance, is such a performance metric. ...
Hui Li, David L. Groep, Lex Wolters
ICML
2000
IEEE
14 years 8 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
ECCV
2004
Springer
14 years 9 months ago
Decision Theoretic Modeling of Human Facial Displays
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Jesse Hoey, James J. Little
ECAI
2000
Springer
13 years 12 months ago
Data Set Editing by Ordered Projection
In this paper, an editing algorithm based on the projection of the examples in each dimension is presented. The algorithm, that we have called EOP (Editing by Ordered Projection) h...
Jesús S. Aguilar-Ruiz, José Crist&oa...