Sparse LDA (Matlab implementation)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F06%3A00078467" target="_blank" >RIV/67985807:_____/06:00078467 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Sparse LDA (Matlab implementation)
Original language description
This is the MATLAB implementation of an algorithm for classification with FLDA designed for the high-dimensional/small sample size setting, exploiting among others sparsity. It is described in detail in our paper "Improving Implementation of Linear Discriminant Analysis for the High Dimension/ Small Sample Size Problem"', by J. Duintjer Tebbens and P. Schlesinger, to appear in CSDA in 2007.
Czech name
Sparse LDA (implementace v Matlabu)
Czech description
Jedná se o implementaci algoritmu pro klasifikaci pomocí metody FLDA v Matlabu. Metoda je koncipována pro situace, kde vzniká tzv. small sample size problem, algoritmus využívá mimo jiné řídkost matic. Více podrobností je v našem článku "Improving Implementation of Linear Discriminant Analysis for the High Dimension/ Small Sample Size Problem", J. Duintjer Tebbens and P. Schlesinger, který bude publikován v časopise CSDA v roce 2007.
Classification
Type
X - Unclassified
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1ET400300415" target="_blank" >1ET400300415: Modelling and simulation of complex technical problems:effective numerical algorithms and parallel implementation using new information technologie</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů