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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 6 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
SGAI
2009
Springer
14 years 15 days ago
Parallel Rule Induction with Information Theoretic Pre-Pruning
In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to indu...
Frederic T. Stahl, Max Bramer, Mo Adda
DSN
2007
IEEE
14 years 9 days ago
Utilizing Dynamically Coupled Cores to Form a Resilient Chip Multiprocessor
Aggressive CMOS scaling will make future chip multiprocessors (CMPs) increasingly susceptible to transient faults, hard errors, manufacturing defects, and process variations. Exis...
Christopher LaFrieda, Engin Ipek, José F. M...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 6 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
13 years 9 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...