71 search results - page 2 / 15 » An evaluation of dimension reduction techniques for one-clas... |
ADMA
2008
Springer
13 years 9 months ago
2008
Springer
We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
HIS
2001
13 years 9 months ago
2001
Abstract. Linear Discriminant (LD) techniques are typically used in pattern recognition tasks when there are many (n >> 104 ) datapoints in low-dimensional (d < 102 ) spac...
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
CISIM
2008
IEEE
14 years 2 months ago
2008
IEEE
In this paper, we compare performance of several dimension reduction techniques, namely SVD, NMF and SDD.The qualitative comparison is evaluated on a collection of bars. We compare...