Using data mining for wine quality assessment

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5808 LNAI, Issue , 2009, Pages 66-79

  Cortez, Paulo ^a   Teixeira, Juliana ^a   Cerdeira, António ^b   Almeida, Fernando ^b   Matos, Telmo ^b   Reis, José ^a,b  

^a UNIVERSITY OF MINHO   (Portugal)

^b Viticulture Commission of the Vinho Verde Region (CVRVV)   (Portugal)

Author keywords

Ordinal Regression; Sensitivity Analysis; Sensory Preferences; Support Vector Machines; Variable and Model Selection; Wine Science

Indexed keywords

ALCOHOL LEVELS; ANALYTICAL TESTS; COMPUTATIONALLY EFFICIENT; DATA SETS; EXPERT EVALUATION; HUMAN EXPERT; INPUT VARIABLES; MODEL SELECTION; MULTIPLE REGRESSIONS; NEURAL NETWORK METHOD; ORDINAL REGRESSION; PHYSICO-CHEMICAL TEST; PORTUGAL; QUALITY ASSESSMENT; REGRESSION TECHNIQUES; SENSORY PREFERENCES; VARIABLE AND MODEL SELECTION; WINE INDUSTRY; WINE QUALITY;

DIELECTRIC RELAXATION; GEARS; MULTILAYER NEURAL NETWORKS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; WINE;

SENSITIVITY ANALYSIS;

EID: 71049191103     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04747-3_8     Document Type: Conference Paper

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