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» Numbers in Multi-relational Data Mining
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SDM
2008
SIAM
165views Data Mining» more  SDM 2008»
15 years 6 months ago
On the Dangers of Cross-Validation. An Experimental Evaluation
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
R. Bharat Rao, Glenn Fung
ICDM
2006
IEEE
107views Data Mining» more  ICDM 2006»
15 years 11 months ago
Improving Grouped-Entity Resolution Using Quasi-Cliques
The entity resolution (ER) problem, which identifies duplicate entities that refer to the same real world entity, is essential in many applications. In this paper, in particular,...
Byung-Won On, Ergin Elmacioglu, Dongwon Lee, Jaewo...
KDD
2001
ACM
156views Data Mining» more  KDD 2001»
16 years 5 months ago
A Customer Purchase Incidence Model Applied to Recommender Services
In this contribution we transfer a customer purchase incidence model for consumer products which is based on Ehrenberg's repeat-buying theory to Web-based information products...
Andreas Geyer-Schulz, Michael Hahsler, Maximillian...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 11 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
RSFDGRC
2009
Springer
15 years 11 months ago
Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis
Abstract. Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various ...
Qiang Shen