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KDD
2009
ACM
158views Data Mining» more  KDD 2009»
16 years 6 months ago
Feature shaping for linear SVM classifiers
: ? Feature Shaping for Linear SVM Classifiers George Forman, Martin Scholz, Shyamsundar Rajaram HP Laboratories HPL-2009-31R1 text classification machine learning, feature weighti...
George Forman, Martin Scholz, Shyamsundar Rajaram
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
16 years 6 months ago
Empirical comparisons of various voting methods in bagging
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Kelvin T. Leung, Douglas Stott Parker Jr.
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
16 years 6 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
SIGMOD
2005
ACM
119views Database» more  SIGMOD 2005»
16 years 6 months ago
Update-Pattern-Aware Modeling and Processing of Continuous Queries
A defining characteristic of continuous queries over on-line data streams, possibly bounded by sliding windows, is the potentially infinite and time-evolving nature of their input...
Lukasz Golab, M. Tamer Özsu
ECAI
2008
Springer
15 years 8 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo