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GECCO
2004
Springer
127views Optimization» more  GECCO 2004»
15 years 11 months ago
Improved Niching and Encoding Strategies for Clustering Noisy Data Sets
Clustering is crucial to many applications in pattern recognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most su...
Olfa Nasraoui, Elizabeth Leon
KDD
1995
ACM
95views Data Mining» more  KDD 1995»
15 years 9 months ago
Limits on Learning Machine Accuracy Imposed by Data Quality
Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the ...
Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chian...
KDD
1995
ACM
248views Data Mining» more  KDD 1995»
15 years 9 months ago
Data Mining for Loan Evaluation at ABN AMRO: A Case Study
Wedescribe a case study in data miningfor personal loan evaluation, performed at the ABNAMRObank in the Netherlands. Historical data of clients and their pay-backbehaviourare used...
A. J. Feelders, A. J. F. le Loux, J. W. van't Zand
ICS
2009
Tsinghua U.
15 years 10 months ago
A translation system for enabling data mining applications on GPUs
Modern GPUs offer much computing power at a very modest cost. Even though CUDA and other related recent developments are accelerating the use of GPUs for general purpose applicati...
Wenjing Ma, Gagan Agrawal
158
Voted
FGCS
2007
160views more  FGCS 2007»
15 years 5 months ago
Distributed data mining in grid computing environments
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an e...
Ping Luo, Kevin Lü, Zhongzhi Shi, Qing He