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KDD
2004
ACM
154views Data Mining» more  KDD 2004»
16 years 5 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
115
Voted
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
16 years 5 months ago
Mining coherent gene clusters from gene-sample-time microarray data
Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of genesa...
Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tan...
125
Voted
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 5 months ago
Dense itemsets
Frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. In this paper we address a problem with frequen...
Heikki Mannila, Jouni K. Seppänen
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 5 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
2002
ACM
145views Data Mining» more  KDD 2002»
16 years 5 months ago
Handling very large numbers of association rules in the analysis of microarray data
The problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for ...
Alexander Tuzhilin, Gediminas Adomavicius
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