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DATAMINE
2002
125views more  DATAMINE 2002»
13 years 7 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
13 years 11 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
13 years 11 months ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh
ICDM
2003
IEEE
136views Data Mining» more  ICDM 2003»
14 years 19 days ago
Statistical Relational Learning for Document Mining
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 21 days ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez