Penalised Reduction & Classification Toolbox

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F16%3A00088847" target="_blank" >RIV/00216224:14110/16:00088847 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Penalised Reduction & Classification Toolbox
Original language description
Penalised Reduction & Classification Toolbox provides algorithms for reduction and classification of various types of data, such as genetic data, two-dimensional (2-D) face image data or three-dimensional (3-D) brain image data. The algorithms were implemented as functions in MATLAB environment. Nowadays, the toolbox enables reduction of data by selecting most discriminative features using penalised linear discriminant analysis (pLDA) with resampling, penalised linear regression (pLR) with resampling, and t-test or feature extraction using intersubject principal component analysis (isPCA). The reduced data are then classified into two groups using linear discriminant analysis (LDA) or linear support vector machines (SVM). Classification performance of methods acquired by leave-one-out cross-validation can be compared using the McNemar’s test.
Czech name
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Czech description
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Project
<a href="/en/project/NT13359" target="_blank" >NT13359: Advanced Methods for Recognition of MR brain images for Computer Aided Diagnosis of Neuropsychiatric Disorders</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Internal product ID
Penalised Toolbox
Technical parameters
Eva Janoušová, Masarykova univerzita, Kamenice 126/3, Brno, janousova@iba.muni.cz
Economical parameters
Software je volně dostupný na uvedené webové adrese a implementovatelny v prostředí MATLAB
Owner IČO
00216224
Owner name
Masarykova univerzita

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