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» Dimensionality Reduction for Classification
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PR
2006
87views more  PR 2006»
15 years 3 months ago
Prototype reduction schemes applicable for non-stationary data sets
All of the prototype reduction schemes (PRS) which have been reported in the literature, process time-invariant data to yield a subset of prototypes that are useful in nearest-nei...
Sang-Woon Kim, B. John Oommen
BMCBI
2010
151views more  BMCBI 2010»
15 years 3 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
205
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ICML
2004
IEEE
16 years 4 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
ICIP
2007
IEEE
16 years 5 months ago
Projection onto a Shape Manifold for Image Segmentation with Prior
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
Florent Ségonne, Patrick Etyngier, Renaud K...
APVIS
2008
15 years 4 months ago
A Novel Visualization System for Expressive Facial Motion Data Exploration
Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensional...
Tanasai Sucontphunt, Xiaoru Yuan, Qing Li, Zhigang...