Multivariate feature selection and hierarchical classification for infrared spectroscopy: Serum-based detection of bovine spongiform encephalopathy

Analytical and Bioanalytical Chemistry

Volumn 387, Issue 5, 2007, Pages 1801-1807

  Menze, Bjoern H ^a   Petrich, Wolfgang ^a,b   Hamprecht, Fred A ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b ROCHE DIAGNOSTICS GMBH   (Germany)

Author keywords

Diagnostic pattern recognition; Feature selection; Gini importance; Hierarchical classification; Random forest

Indexed keywords

BIODIVERSITY; FORESTRY; INFRARED SPECTROSCOPY; PATTERN RECOGNITION;

DIAGNOSTIC PATTERN RECOGNITION; GINI IMPORTANCE; HIERARCHICAL CLASSIFICATION; RANDOM FORESTS;

NEUROLOGY;

ANIMAL; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BLOOD; BLOOD ANALYSIS; BOVINE SPONGIFORM ENCEPHALOPATHY; CATTLE; COMPUTER ASSISTED DIAGNOSIS; CONFERENCE PAPER; INFRARED SPECTROPHOTOMETRY; METHODOLOGY; MULTIVARIATE ANALYSIS;

ANIMALS; ARTIFICIAL INTELLIGENCE; BLOOD CHEMICAL ANALYSIS; CATTLE; DIAGNOSIS, COMPUTER-ASSISTED; ENCEPHALOPATHY, BOVINE SPONGIFORM; MULTIVARIATE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; SPECTROPHOTOMETRY, INFRARED;

BIODIVERSITY; FORESTS; INFRARED SPECTROSCOPY; NEUROLOGY; PATTERN RECOGNITION;

BOS; BOVINAE;

EID: 33847236254     PISSN: 16182642     EISSN: 16182650     Source Type: Journal    
DOI: 10.1007/s00216-006-1070-5     Document Type: Conference Paper

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