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ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
16 years 10 days ago
Localized Prediction of Continuous Target Variables Using Hierarchical Clustering
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
ICDM
2003
IEEE
102views Data Mining» more  ICDM 2003»
16 years 10 days ago
Bootstrapping Rule Induction
Most rule learning systems posit hard decision boundaries for continuous attributes and point estimates of rule accuracy, with no measures of variance, which may seem arbitrary to ...
Lemuel R. Waitman, Douglas H. Fisher, Paul H. King
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
16 years 15 hour ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 11 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
KDD
2010
ACM
282views Data Mining» more  KDD 2010»
15 years 11 months ago
Optimizing debt collections using constrained reinforcement learning
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....