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» Data mining, Hypergraph Transversals, and Machine Learning
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KDD
2005
ACM
161views Data Mining» more  KDD 2005»
14 years 9 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
ALGORITHMICA
2010
95views more  ALGORITHMICA 2010»
13 years 8 months ago
Homogeneous String Segmentation using Trees and Weighted Independent Sets
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
Peter Damaschke
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
2005
ACM
130views Data Mining» more  KDD 2005»
14 years 9 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
AIED
2009
Springer
14 years 3 months ago
Detecting the Learning Value of Items In a Randomized Problem Set
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
Zachary A. Pardos, Neil T. Heffernan