Agroclimatic classification: numerical- taxonomic procedures - a review.
Autor(a) principal: | |
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Data de Publicação: | 1983 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/132990 |
Resumo: | The paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree. |
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Agroclimatic classification: numerical- taxonomic procedures - a review.ClassificacaoAgroclimaticClimaticClimaAgriculturaClimatologiaclassificationThe paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree.S. JEEVANANDA REDDY, CPATSA - Consultor.REDDY, S. J.2016-05-31T11:13:34Z2016-05-31T11:13:34Z1996-07-0919832016-05-31T11:13:34Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlePesquisa Agropecuária Brasileira, Brasília, DF, v. 18, n. 5, p. 435-457, 1983.http://www.alice.cnptia.embrapa.br/alice/handle/doc/132990enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T02:57:50Zoai:www.alice.cnptia.embrapa.br:doc/132990Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T02:57:50falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T02:57:50Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
title |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
spellingShingle |
Agroclimatic classification: numerical- taxonomic procedures - a review. REDDY, S. J. Classificacao Agroclimatic Climatic Clima Agricultura Climatologia classification |
title_short |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
title_full |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
title_fullStr |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
title_full_unstemmed |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
title_sort |
Agroclimatic classification: numerical- taxonomic procedures - a review. |
author |
REDDY, S. J. |
author_facet |
REDDY, S. J. |
author_role |
author |
dc.contributor.none.fl_str_mv |
S. JEEVANANDA REDDY, CPATSA - Consultor. |
dc.contributor.author.fl_str_mv |
REDDY, S. J. |
dc.subject.por.fl_str_mv |
Classificacao Agroclimatic Climatic Clima Agricultura Climatologia classification |
topic |
Classificacao Agroclimatic Climatic Clima Agricultura Climatologia classification |
description |
The paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree. |
publishDate |
1983 |
dc.date.none.fl_str_mv |
1983 1996-07-09 2016-05-31T11:13:34Z 2016-05-31T11:13:34Z 2016-05-31T11:13:34Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 18, n. 5, p. 435-457, 1983. http://www.alice.cnptia.embrapa.br/alice/handle/doc/132990 |
identifier_str_mv |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 18, n. 5, p. 435-457, 1983. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/132990 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503421700603904 |