125 search results - page 4 / 25 » Rotational Linear Discriminant Analysis Technique for Dimens... |
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
IEEEMM
2007
13 years 5 months ago
2007
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
NIPS
2004
13 years 7 months ago
2004
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
VLSISP
2002
13 years 5 months ago
2002
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...