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» Learning Rules from Distributed Data
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HPDC
2010
IEEE
15 years 25 days ago
Lessons learned from moving earth system grid data sets over a 20 Gbps wide-area network
In preparation for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, the climate community will run the Coupled Model Intercomparison Project phase 5 (...
Rajkumar Kettimuthu, Alex Sim, Dan Gunter, Bill Al...
SAC
2005
ACM
15 years 5 months ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...
KDD
1998
ACM
112views Data Mining» more  KDD 1998»
15 years 4 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
KELSI
2004
Springer
15 years 5 months ago
Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets
There is an overwhelming increase in submissions to genomic databases, posing a problem for database maintenance, especially regarding annotation of fields left blank during submi...
Gustavo E. A. P. A. Batista, Maria Carolina Monard...
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
15 years 1 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà