Penalised Reduction & Classification Toolbox

JANOUŠOVÁ, Eva. Penalised Reduction & Classification Toolbox. 2016.

Basic information

• Original name: Penalised Reduction & Classification Toolbox
• Authors: JANOUŠOVÁ, Eva (203 Czech Republic, guarantor, belonging to the institution).
• Edition: 2016.

Other information

• Original language: English
• Type of outcome: Software
• Field of Study: 30000 3. Medical and Health Sciences
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• RIV identification code: RIV/00216224:14110/16:00088847
• Organization unit: Faculty of Medicine
• Keywords in English: neuroimaging; software; brain; classification
• Technical parameters: Eva Janoušová, Masarykova univerzita, Kamenice 126/3, Brno, [e-mail]
• Tags: EL OK

Abstract

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.

Links

• NT13359, research and development project: Name: Pokročilé metody rozpoznávání MR obrazů mozku pro podporu diagnostiky neuropsychiatrických poruch

Investor: Ministry of Health of the CR