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PAKDD
2000
ACM
140views Data Mining» more  PAKDD 2000»
15 years 3 months ago
Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases
The objective of data reduction is to obtain a compact representation of a large data set to facilitate repeated use of non-redundant information with complex and slow learning alg...
Slobodan Vucetic, Zoran Obradovic
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 3 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
PAKDD
2010
ACM
167views Data Mining» more  PAKDD 2010»
15 years 3 months ago
Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand
We present a general framework for the task of extracting specific information “on demand” from a large corpus such as the Web under resource-constraints. Given a database wit...
Pallika Kanani, Andrew McCallum, Shaohan Hu
SDM
2010
SIAM
218views Data Mining» more  SDM 2010»
15 years 1 months ago
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
SDM
2008
SIAM
136views Data Mining» more  SDM 2008»
15 years 1 months ago
Exploration and Reduction of the Feature Space by Hierarchical Clustering
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
Dino Ienco, Rosa Meo