Predicting wine quality from terrain characteristics with regression trees

Predicting wine quality from terrain characteristics with regression trees

A former cartographic study on terrain characteristics of the German Rhinegau is reviewed. An attempt is made to predict relative quality of the Riesling from local site factors usings Classifcation And Regression Trees (= CART). Valid results suppose quantity to be ruled out by quality, ignoring an...

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Bibliographic Details
Main Author: Reiner Schwarz
Format: Article
Language:deu
Published: Unité Mixte de Recherche 8504 Géographie-cités 1997-11-01
Series:Cybergeo
Subjects:
wine quality
terrain characteristic
regression classification
statistics
agriculture
vineyard ecology
Online Access:http://journals.openedition.org/cybergeo/361
id doaj-b5b3d31014e546a09fd5faa50881dec8
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spelling doaj-b5b3d31014e546a09fd5faa50881dec82021-10-05T13:16:37ZdeuUnité Mixte de Recherche 8504 Géographie-citésCybergeo1278-33661997-11-0110.4000/cybergeo.361Predicting wine quality from terrain characteristics with regression treesReiner SchwarzA former cartographic study on terrain characteristics of the German Rhinegau is reviewed. An attempt is made to predict relative quality of the Riesling from local site factors usings Classifcation And Regression Trees (= CART). Valid results suppose quantity to be ruled out by quality, ignoring any price ratio of vine cultivation. The study demonstrates that CART is a valuable statistical tool without restrictions by data types.http://journals.openedition.org/cybergeo/361wine qualityterrain characteristicregression classificationstatisticsagriculturevineyard ecology
collection DOAJ
language deu
format Article
sources DOAJ
author Reiner Schwarz
spellingShingle Reiner Schwarz
Predicting wine quality from terrain characteristics with regression trees
Cybergeo
wine quality
terrain characteristic
regression classification
statistics
agriculture
vineyard ecology
author_facet Reiner Schwarz
author_sort Reiner Schwarz
title Predicting wine quality from terrain characteristics with regression trees
title_short Predicting wine quality from terrain characteristics with regression trees
title_full Predicting wine quality from terrain characteristics with regression trees
title_fullStr Predicting wine quality from terrain characteristics with regression trees
title_full_unstemmed Predicting wine quality from terrain characteristics with regression trees
title_sort predicting wine quality from terrain characteristics with regression trees
publisher Unité Mixte de Recherche 8504 Géographie-cités
series Cybergeo
issn 1278-3366
publishDate 1997-11-01
description A former cartographic study on terrain characteristics of the German Rhinegau is reviewed. An attempt is made to predict relative quality of the Riesling from local site factors usings Classifcation And Regression Trees (= CART). Valid results suppose quantity to be ruled out by quality, ignoring any price ratio of vine cultivation. The study demonstrates that CART is a valuable statistical tool without restrictions by data types.
topic wine quality
terrain characteristic
regression classification
statistics
agriculture
vineyard ecology
url http://journals.openedition.org/cybergeo/361
work_keys_str_mv AT reinerschwarz predictingwinequalityfromterraincharacteristicswithregressiontrees
_version_ 1716841936716824576

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