๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Kernel density classification and boosting: an L2analysis

โœ Scribed by M. Di Marzio; C. C. Taylor


Book ID
106537106
Publisher
Springer US
Year
2005
Tongue
English
Weight
866 KB
Volume
15
Category
Article
ISSN
0960-3174

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


The improvement of SIMCA classification
โœ Hilko vander Voet; Durk A. Doornbos ๐Ÿ“‚ Article ๐Ÿ“… 1984 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 664 KB

The performance of the new probabilistic classification method CLASSY is evaluated on three different data sets, together with its predecessors SIMCA and ALLOC. The improvement made over ALLOC is only marginal, whereas CLASSY shows better predictive ability and greater reliability than SIMCA in most

The improvement of SIMCA classification
โœ Hilko van der Voet; Durk A. Doornbos ๐Ÿ“‚ Article ๐Ÿ“… 1984 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 661 KB

One of the disadvantages of SIMCA pattern recognition is its inability to produce probabilistic classifications. Attempts to correct this involve distributional assumptions. It appears that SIMCA can handle the residual error terms efficiently, but that inside the class model subspace a crude trunca