2712 search results - page 13 / 543 » On learning algorithm selection for classification |
HIS
2004
13 years 9 months ago
2004
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
ICMLA
2008
13 years 9 months ago
2008
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
FSKD
2008
Springer
13 years 8 months ago
2008
Springer
This paper presents a scheme for unsupervised classification with Gaussian mixture models by means of statistical learning analysis. A Bayesian Ying-Yang harmony learning system a...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Meta-Learning has been used to select algorithms based on the features of the problems being tackled. Each training example in this context, i.e. each meta-example, stores the feat...
CIVR
2008
Springer
13 years 9 months ago
2008
Springer
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...