181 search results - page 1 / 37 » Worst-Case Analysis of Selective Sampling for Linear Classif... |
JMLR
2006
13 years 4 months ago
2006
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
NIPS
2004
13 years 6 months ago
2004
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
NIPS
2008
13 years 6 months ago
2008
We provide a new analysis of an efficient margin-based algorithm for selective sampling in classification problems. Using the so-called Tsybakov low noise condition to parametrize...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
CSB
2005
IEEE
13 years 6 months ago
2005
IEEE
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...