209 search results - page 11 / 42 » Evaluating Feature Selection for SVMs in High Dimensions |
EWCBR
2006
Springer
15 years 2 months ago
2006
Springer
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
TIFS
2008
14 years 10 months ago
2008
Poor quality images can significantly affect the accuracy of iris-recognition systems because they do not have enough feature information. However, existing quality measures have f...
101
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BMCBI
2004
14 years 10 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...
ICDE
2007
IEEE
15 years 4 months ago
2007
IEEE
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
102
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TRECVID
2007
14 years 11 months ago
2007
This paper describes our experiments for the high level feature extraction task in TRECVid 2007. We submitted the following five runs: • A jr1 1: Baseline run using early fusio...