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» Model-based Boosting 2.0
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KDD
2004
ACM
181views Data Mining» more  KDD 2004»
14 years 8 months ago
Column-generation boosting methods for mixture of kernels
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Jinbo Bi, Tong Zhang, Kristin P. Bennett
JCISD
2006
114views more  JCISD 2006»
13 years 7 months ago
Ensemble of Linear Models for Predicting Drug Properties
We propose a new classification method for prediction of drug properties, called the Random Feature Subset Boosting for Linear Discriminant Analysis (LDA). The main novelty of this...
Tomasz Arodz, David A. Yuen, Arkadiusz Z. Dudek
CEC
2008
IEEE
14 years 2 months ago
NichingEDA: Utilizing the diversity inside a population of EDAs for continuous optimization
— Since the Estimation of Distribution Algorithms (EDAs) have been introduced, several single model based EDAs and mixture model based EDAs have been developed. Take Gaussian mod...
Weishan Dong, Xin Yao
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 9 days ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
WABI
2007
Springer
123views Bioinformatics» more  WABI 2007»
14 years 1 months ago
Inverse Sequence Alignment from Partial Examples
When aligning biological sequences, the choice of parameter values for the alignment scoring function is critical. Small changes in gap penalties, for example, can yield radically ...
Eagu Kim, John D. Kececioglu