6 search results - page 1 / 2 » Discovery of Relevant Weights by Minimizing Cross-Validation... |
PAKDD
2000
ACM
13 years 11 months ago
2000
ACM
In order to discover relevant weights of neural networks, this paper proposes a novel method to learn a distinct squared penalty factor for each weight as a minimization problem ov...
ICML
1994
IEEE
13 years 11 months ago
1994
IEEE
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
NECO
1998
13 years 7 months ago
1998
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
PR
2006
13 years 7 months ago
2006
A cross-validation error estimator is obtained by repeatedly leaving out some data points, deriving classifiers on the remaining points, computing errors for these classifiers on ...
PR
2008
13 years 7 months ago
2008
The error correcting output codes (ECOC) technique is a useful way to extend any binary classifier to the multiclass case. The design of an ECOC matrix usually considers an a prio...