148 search results - page 24 / 30 » DiscLDA: Discriminative Learning for Dimensionality Reductio... |
BMCBI
2006
13 years 7 months ago
2006
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
PAA
2002
13 years 7 months ago
2002
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
KDD
2004
ACM
14 years 8 months ago
2004
ACM
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...