Sciweavers

1160 search results - page 10 / 232
» Combined regression and ranking
Sort
View
CEC
2011
IEEE
12 years 9 months ago
Trainer selection strategies for coevolving rank predictors
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
Daniel L. Ly, Hod Lipson
DMIN
2007
91views Data Mining» more  DMIN 2007»
13 years 11 months ago
Instance Ranking using Ensemble Spread
- This paper investigates a technique for predicting ensemble uncertainty originally proposed in the weather forecasting domain. The overall purpose is to find out if the technique...
Rikard König, Ulf Johansson, Lars Niklasson
ICDM
2005
IEEE
134views Data Mining» more  ICDM 2005»
14 years 3 months ago
A Preference Model for Structured Supervised Learning Tasks
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
Fabio Aiolli
ICML
2005
IEEE
14 years 10 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
MCS
2009
Springer
14 years 2 months ago
An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets
The meta-learner MLR (Multi-response Linear Regression) has been proposed as a trainable combiner for fusing heterogeneous baselevel classifiers. Although it has interesting prope...
Chun-Xia Zhang, Robert P. W. Duin