107 search results - page 10 / 22 » Dimensionality reduction by unsupervised regression |
SADM
2010
13 years 2 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
ISDA
2009
IEEE
14 years 2 months ago
2009
IEEE
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
PR
2006
13 years 7 months ago
2006
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
JMLR
2010
13 years 2 months ago
2010
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...