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» Predicting Future Decision Trees from Evolving Data
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BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
KES
2007
Springer
13 years 7 months ago
KeyGraph-based chance discovery for mobile contents management system
Chance discovery provides a way to find rare but very important events for future decision making. It can be applied to stock market prediction, earthquake alarm, intrusion detect...
Kyung-Joong Kim, Myung-Chul Jung, Sung-Bae Cho
IJCAI
1997
13 years 8 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida
KDD
1997
ACM
122views Data Mining» more  KDD 1997»
13 years 11 months ago
Computing Optimized Rectilinear Regions for Association Rules
We address the problem of nding useful regions for two-dimensional association rules and decision trees. In a previous paper we presented ecient algorithms for computing optimiz...
Kunikazu Yoda, Takeshi Fukuda, Yasuhiko Morimoto, ...
INFOCOM
2003
IEEE
14 years 19 days ago
Static and Dynamic Analysis of the Internet's Susceptibility to Faults and Attacks
— We analyze the susceptibility of the Internet to random faults, malicious attacks, and mixtures of faults and attacks. We analyze actual Internet data, as well as simulated dat...
Seung-Taek Park, Alexy Khrabrov, David M. Pennock,...