429 search results - page 19 / 86 » Unsupervised feature selection for principal components anal... |
NIPS
2000
13 years 9 months ago
2000
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
ICDAR
2009
IEEE
14 years 2 months ago
2009
IEEE
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
ICDAR
2009
IEEE
13 years 5 months ago
2009
IEEE
We report an automatic feature discovery method that achieves results comparable to a manually chosen, larger feature set on a document image content extraction problem: the locat...
JMM2
2008
13 years 7 months ago
2008
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
ICIAP
1999
ACM
13 years 12 months ago
1999
ACM
In this work we propose a new supervised deformable model that generalizes the classical contour-based snake. This model is defined to deform in a feature space generated by a se...