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ESEM
2008
ACM
13 years 9 months ago
Fit data selection for software effort estimation models
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...
Koji Toda, Akito Monden, Ken-ichi Matsumoto
ICCV
2005
IEEE
14 years 1 months ago
Image Based Regression Using Boosting Method
We present a general algorithm of image based regression that is applicable to many vision problems. The proposed regressor that targets a multiple-output setting is learned using...
Shaohua Kevin Zhou, Bogdan Georgescu, Xiang Sean Z...
ML
2002
ACM
129views Machine Learning» more  ML 2002»
13 years 7 months ago
Model Selection for Small Sample Regression
Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...
Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio
CIKM
2010
Springer
13 years 5 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
ICML
2007
IEEE
14 years 8 months ago
An integrated approach to feature invention and model construction for drug activity prediction
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
David Page, Jesse Davis, Soumya Ray, Vítor ...