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» An e-Process Selection Model
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ICML
2000
IEEE
16 years 5 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
CVPR
2010
IEEE
16 years 27 days ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
IROS
2008
IEEE
156views Robotics» more  IROS 2008»
15 years 11 months ago
Bayesian state estimation and behavior selection for autonomous robotic exploration in dynamic environments
— In order to be truly autonomous, robots that operate in natural, populated environments must have the ability to create a model of these unpredictable dynamic environments and ...
Georgios Lidoris, Dirk Wollherr, Martin Buss
CEC
2010
IEEE
15 years 6 months ago
An analysis of clustering objectives for feature selection applied to encrypted traffic identification
This work explores the use of clustering objectives in a Multi-Objective Genetic Algorithm (MOGA) for both, feature selection and cluster count optimization, under the application...
Carlos Bacquet, A. Nur Zincir-Heywood, Malcolm I. ...
CSDA
2006
96views more  CSDA 2006»
15 years 5 months ago
Analysis of new variable selection methods for discriminant analysis
Several methods to select variables that are subsequently used in discriminant analysis are proposed and analysed. The aim is to find from among a set of m variables a smaller sub...
Joaquín A. Pacheco, Silvia Casado, Laura N&...