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» Boosting Methods for Regression
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TNN
2010
127views Management» more  TNN 2010»
13 years 4 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia
BMCBI
2007
144views more  BMCBI 2007»
13 years 10 months ago
Robust regression for periodicity detection in non-uniformly sampled time-course gene expression data
Background: In practice many biological time series measurements, including gene microarrays, are conducted at time points that seem to be interesting in the biologist's opin...
Miika Ahdesmäki, Harri Lähdesmäki, ...
BMCBI
2008
159views more  BMCBI 2008»
13 years 10 months ago
Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via log
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
Dawei Liu, Debashis Ghosh, Xihong Lin
EOR
2008
99views more  EOR 2008»
13 years 10 months ago
Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
KES
2005
Springer
14 years 3 months ago
A SVM Regression Based Approach to Filling in Missing Values
In KDD procedure, to fill in missing data typically requires a very large investment of time and energy - often 80% to 90% of a data analysis project is spent in making the data re...
Honghai Feng, Chen Guoshun, Yin Cheng, Bingru Yang...