29 search results - page 1 / 6 » Active sampling for detecting irrelevant features |
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
AI
2004
Springer
13 years 4 months ago
2004
Springer
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
IJCNN
2008
IEEE
13 years 10 months ago
2008
IEEE
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
BMCBI
2004
13 years 4 months ago
2004
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
KI
2007
Springer
13 years 4 months ago
2007
Springer
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...