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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 9 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
KDD
2004
ACM
179views Data Mining» more  KDD 2004»
14 years 9 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
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 9 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 9 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
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