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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 10 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2006
ACM
253views Data Mining» more  KDD 2006»
14 years 10 months ago
Adaptive Website Design Using Caching Algorithms
Visitors enter a website through a variety of means, including web searches, links from other sites, and personal bookmarks. In some cases the first page loaded satisfies the visi...
Justin Brickell, Inderjit S. Dhillon, Dharmendra S...
KDD
2008
ACM
213views Data Mining» more  KDD 2008»
14 years 10 months ago
Heterogeneous data fusion for alzheimer's disease study
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...
KDD
2004
ACM
179views Data Mining» more  KDD 2004»
14 years 10 months ago
1-dimensional splines as building blocks for improving accuracy of risk outcomes models
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
David S. Vogel, Morgan C. Wang
IJCNN
2008
IEEE
14 years 4 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...