{"id":"https://openalex.org/W3089720541","doi":"https://doi.org/10.1007/978-3-030-58799-4_38","title":"Classification of Carcass Fatness Degree in Finishing Cattle Using Machine Learning","display_name":"Classification of Carcass Fatness Degree in Finishing Cattle Using Machine Learning","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3089720541","doi":"https://doi.org/10.1007/978-3-030-58799-4_38","mag":"3089720541"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-58799-4_38","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-58799-4_38","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074654556","display_name":"Higor Henrique Picoli Nucci","orcid":"https://orcid.org/0000-0003-4886-6041"},"institutions":[{"id":"https://openalex.org/I122558511","display_name":"Universidade Federal de Mato Grosso do Sul","ror":"https://ror.org/0366d2847","country_code":"BR","type":"education","lineage":["https://openalex.org/I122558511"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Higor Henrique Picoli Nucci","raw_affiliation_strings":["Federal University of Mato Grosso do Sul, Campo Grande, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-4886-6041","affiliations":[{"raw_affiliation_string":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","institution_ids":["https://openalex.org/I122558511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047727871","display_name":"Renato Porf\u00edrio Ishii","orcid":"https://orcid.org/0000-0003-0825-8420"},"institutions":[{"id":"https://openalex.org/I122558511","display_name":"Universidade Federal de Mato Grosso do Sul","ror":"https://ror.org/0366d2847","country_code":"BR","type":"education","lineage":["https://openalex.org/I122558511"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Renato Porfirio Ishii","raw_affiliation_strings":["Federal University of Mato Grosso do Sul, Campo Grande, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-0825-8420","affiliations":[{"raw_affiliation_string":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","institution_ids":["https://openalex.org/I122558511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081895375","display_name":"Rodrigo da Costa Gomes","orcid":"https://orcid.org/0000-0001-8410-7216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rodrigo da Costa\u00a0Gomes","raw_affiliation_strings":["Embrapa Gado de Corte, Campo Grande, Mato Grosso do Sul, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-8410-7216","affiliations":[{"raw_affiliation_string":"Embrapa Gado de Corte, Campo Grande, Mato Grosso do Sul, Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057248082","display_name":"Celso Soares Costa","orcid":"https://orcid.org/0000-0001-7040-7058"},"institutions":[{"id":"https://openalex.org/I44839336","display_name":"Universidade Cat\u00f3lica Dom Bosco","ror":"https://ror.org/02q070r42","country_code":"BR","type":"education","lineage":["https://openalex.org/I44839336"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Celso Soares Costa","raw_affiliation_strings":["Federal Institute of Education, Science and Technology of Mato Grosso do Sul, Campo Grande, Brazil","Universidade Cat\u00f3lica Dom Bosco, Campo Grande, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-7040-7058","affiliations":[{"raw_affiliation_string":"Federal Institute of Education, Science and Technology of Mato Grosso do Sul, Campo Grande, Brazil","institution_ids":[]},{"raw_affiliation_string":"Universidade Cat\u00f3lica Dom Bosco, Campo Grande, Brazil","institution_ids":["https://openalex.org/I44839336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029804824","display_name":"G. L. D. Feij\u00f3","orcid":"https://orcid.org/0000-0003-0278-1755"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gelson Lu\u00eds Dias Feij\u00f3","raw_affiliation_strings":["Embrapa Gado de Corte, Campo Grande, Mato Grosso do Sul, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-0278-1755","affiliations":[{"raw_affiliation_string":"Embrapa Gado de Corte, Campo Grande, Mato Grosso do Sul, Brazil","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16930693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"519","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9218000173568726,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9218000173568726,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9077000021934509,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12388","display_name":"Identification and Quantification in Food","score":0.9021000266075134,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.684911847114563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6745606660842896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6543651819229126},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.6475812196731567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6308637261390686},{"id":"https://openalex.org/keywords/beef-cattle","display_name":"Beef cattle","score":0.47283607721328735},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4628647267818451},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.436704158782959},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.42656630277633667},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4186941385269165},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.41814249753952026},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4170437753200531},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3581070899963379},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18726694583892822},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11097955703735352},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.10083568096160889}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.684911847114563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6745606660842896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6543651819229126},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.6475812196731567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6308637261390686},{"id":"https://openalex.org/C2780505807","wikidata":"https://www.wikidata.org/wiki/Q1208989","display_name":"Beef cattle","level":2,"score":0.47283607721328735},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4628647267818451},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.436704158782959},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.42656630277633667},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4186941385269165},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.41814249753952026},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4170437753200531},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3581070899963379},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18726694583892822},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11097955703735352},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.10083568096160889}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-030-58799-4_38","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-58799-4_38","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","score":0.5099999904632568,"display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W154893689","https://openalex.org/W1584308190","https://openalex.org/W1993220166","https://openalex.org/W2028276885","https://openalex.org/W2061272711","https://openalex.org/W2092829070","https://openalex.org/W2101234009","https://openalex.org/W2101807845","https://openalex.org/W2107686700","https://openalex.org/W2116224763","https://openalex.org/W2148143831","https://openalex.org/W2149298154","https://openalex.org/W2262267227","https://openalex.org/W2403156809","https://openalex.org/W2521200999","https://openalex.org/W2766840421","https://openalex.org/W2791667053","https://openalex.org/W2897344784","https://openalex.org/W2910032679","https://openalex.org/W2990065879","https://openalex.org/W4229725098","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W3183136280","https://openalex.org/W4318559728","https://openalex.org/W2775233965","https://openalex.org/W4360995913","https://openalex.org/W4312193868"],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
