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» Classifier Selection Based on Data Complexity Measures
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APIN
1998
132views more  APIN 1998»
13 years 9 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon
FLAIRS
2000
13 years 11 months ago
Inferencing Bayesian Networks from Time Series Data Using Natural Selection
This paper describes a new framework for using natural selection to evolve Bayesian Networks for use in forecasting time series data. It extends current research by introducing a ...
Andrew J. Novobilski, Farhad Kamangar
JMLR
2008
133views more  JMLR 2008»
13 years 9 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
BIBE
2008
IEEE
112views Bioinformatics» more  BIBE 2008»
13 years 11 months ago
Feature selection and classification for assessment of chronic stroke impairment
Recent advances of robotic/mechanical devices enable us to measure a subject's performance in an objective and precise manner. The main issue of using such devices is how to r...
Jae-Yoon Jung, Janice I. Glasgow, Stephen H. Scott
NIPS
2004
13 years 11 months ago
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
Balázs Kégl, Ligen Wang