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» New ensemble methods for evolving data streams
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CIKM
2006
Springer
14 years 13 days ago
Resource-aware kernel density estimators over streaming data
A fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. For that re...
Christoph Heinz, Bernhard Seeger
COMAD
2009
13 years 9 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
NIPS
2004
13 years 10 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
ICDM
2005
IEEE
179views Data Mining» more  ICDM 2005»
14 years 2 months ago
Bagging with Adaptive Costs
Ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. In this paper, we propose a new algorithm that combine...
Yi Zhang, W. Nick Street
CCE
2006
13 years 8 months ago
New approaches for representing, analyzing and visualizing complex kinetic transformations
Complex kinetic mechanisms involving thousands of reacting species and tens of thousands of reactions are currently required for the rational analysis of modern combustion systems...
Ioannis P. Androulakis