{"id":"https://openalex.org/W2777426921","doi":"https://doi.org/10.1007/978-981-10-7605-3_21","title":"Multiclass Data Classification Using Multinomial Logistic Gaussian Process Model","display_name":"Multiclass Data Classification Using Multinomial Logistic Gaussian Process Model","publication_year":2017,"publication_date":"2017-12-19","ids":{"openalex":"https://openalex.org/W2777426921","doi":"https://doi.org/10.1007/978-981-10-7605-3_21","mag":"2777426921"},"language":"en","primary_location":{"id":"doi:10.1007/978-981-10-7605-3_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-10-7605-3_21","pdf_url":null,"source":{"id":"https://openalex.org/S4210179954","display_name":"Lecture notes in electrical engineering","issn_l":"1876-1100","issn":["1876-1100","1876-1119"],"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 Electrical Engineering","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/A5080070968","display_name":"Wanhyun Cho","orcid":"https://orcid.org/0000-0002-2829-304X"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Wanhyun Cho","raw_affiliation_strings":["Department of Statistics, Chonnam National University, Youngbong-ro 77, Bukgu, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Chonnam National University, Youngbong-ro 77, Bukgu, Gwangju, South Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007533618","display_name":"Soonyoung Park","orcid":null},"institutions":[{"id":"https://openalex.org/I11893660","display_name":"Mokpo National University","ror":"https://ror.org/00v81k483","country_code":"KR","type":"education","lineage":["https://openalex.org/I11893660"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soonyoung Park","raw_affiliation_strings":["Department of Electronics Engineering, Mokpo National University, Yeongsan-ro, Cheonggye-myeon, Muan, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Mokpo National University, Yeongsan-ro, Cheonggye-myeon, Muan, South Korea","institution_ids":["https://openalex.org/I11893660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111386040","display_name":"Sang-Kyoon Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I11893660","display_name":"Mokpo National University","ror":"https://ror.org/00v81k483","country_code":"KR","type":"education","lineage":["https://openalex.org/I11893660"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sangkyoon Kim","raw_affiliation_strings":["Department of Electronics Engineering, Mokpo National University, Yeongsan-ro, Cheonggye-myeon, Muan, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Mokpo National University, Yeongsan-ro, Cheonggye-myeon, Muan, South Korea","institution_ids":["https://openalex.org/I11893660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080070968"],"corresponding_institution_ids":["https://openalex.org/I111277659"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20232034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"126","last_page":"130"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9314000010490417,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9215999841690063,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.7524480819702148},{"id":"https://openalex.org/keywords/multinomial-distribution","display_name":"Multinomial distribution","score":0.6151612401008606},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.589055597782135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5624799728393555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.555716872215271},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5544480681419373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5398985147476196},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5266894102096558},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5089752674102783},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43464338779449463},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.42709848284721375},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.42339026927948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3916301727294922},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38922929763793945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3402462303638458},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32446426153182983},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.22808697819709778}],"concepts":[{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.7524480819702148},{"id":"https://openalex.org/C192065140","wikidata":"https://www.wikidata.org/wiki/Q1147928","display_name":"Multinomial distribution","level":2,"score":0.6151612401008606},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.589055597782135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5624799728393555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.555716872215271},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5544480681419373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5398985147476196},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5266894102096558},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5089752674102783},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43464338779449463},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.42709848284721375},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.42339026927948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3916301727294922},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38922929763793945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3402462303638458},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32446426153182983},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.22808697819709778},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-981-10-7605-3_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-10-7605-3_21","pdf_url":null,"source":{"id":"https://openalex.org/S4210179954","display_name":"Lecture notes in electrical engineering","issn_l":"1876-1100","issn":["1876-1100","1876-1119"],"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 Electrical Engineering","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1746819321","https://openalex.org/W1748359675","https://openalex.org/W2128973832","https://openalex.org/W2139036986","https://openalex.org/W2148319469","https://openalex.org/W2157826563","https://openalex.org/W4211049957"],"related_works":["https://openalex.org/W2494119046","https://openalex.org/W2955220190","https://openalex.org/W1506113033","https://openalex.org/W2369306031","https://openalex.org/W2052791731","https://openalex.org/W3098841390","https://openalex.org/W2784774275","https://openalex.org/W2184978910","https://openalex.org/W1917858188","https://openalex.org/W4214574858"],"abstract_inverted_index":null,"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
