48 search results - page 1 / 10 » Learning a complex metabolomic dataset using random forests ... |
KDD
2004
ACM
14 years 4 months ago
2004
ACM
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
BMCBI
2008
13 years 4 months ago
2008
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
ESANN
2006
13 years 5 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
ECML
2004
Springer
13 years 9 months ago
2004
Springer
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
ISCI
2007
13 years 4 months ago
2007
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...