{"id":"https://openalex.org/W2784219492","doi":"https://doi.org/10.1109/icsai.2017.8248510","title":"Learning decision forest from evidential data: The random training set sampling approach","display_name":"Learning decision forest from evidential data: The random training set sampling approach","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2784219492","doi":"https://doi.org/10.1109/icsai.2017.8248510","mag":"2784219492"},"language":"en","primary_location":{"id":"doi:10.1109/icsai.2017.8248510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"},"type":"article","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/A5065093571","display_name":"Liyao Ma","orcid":"https://orcid.org/0000-0002-4661-1347"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liyao Ma","raw_affiliation_strings":["School of Electrical Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058106175","display_name":"Bin Sun","orcid":"https://orcid.org/0009-0009-2987-2498"},"institutions":[{"id":"https://openalex.org/I52719799","display_name":"Blekinge Institute of Technology","ror":"https://ror.org/0093a8w51","country_code":"SE","type":"education","lineage":["https://openalex.org/I52719799"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Bin Sun","raw_affiliation_strings":["Department of Creative Technologies, Blekinge Institute of Technology, Karlskrona, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Creative Technologies, Blekinge Institute of Technology, Karlskrona, Sweden","institution_ids":["https://openalex.org/I52719799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100732641","display_name":"Chunyan Han","orcid":"https://orcid.org/0000-0001-5809-1740"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyan Han","raw_affiliation_strings":["School of Electrical Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065093571"],"corresponding_institution_ids":["https://openalex.org/I34949971"],"apc_list":null,"apc_paid":null,"fwci":0.9084,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78012468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"1423","last_page":"1428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9940000176429749,"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"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9909999966621399,"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/T10320","display_name":"Neural Networks and Applications","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.7790474891662598},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7197515964508057},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6630430221557617},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.609583854675293},{"id":"https://openalex.org/keywords/simple-random-sample","display_name":"Simple random sample","score":0.5993301272392273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5878705382347107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5775681734085083},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5136322379112244},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5125057697296143},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4806976914405823},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.4438096880912781},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4283015727996826}],"concepts":[{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7790474891662598},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7197515964508057},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6630430221557617},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.609583854675293},{"id":"https://openalex.org/C20353970","wikidata":"https://www.wikidata.org/wiki/Q1056998","display_name":"Simple random sample","level":3,"score":0.5993301272392273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5878705382347107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5775681734085083},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5136322379112244},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5125057697296143},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4806976914405823},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.4438096880912781},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4283015727996826},{"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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai.2017.8248510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W137456267","https://openalex.org/W1500731913","https://openalex.org/W1570448133","https://openalex.org/W1972243481","https://openalex.org/W2007633571","https://openalex.org/W2021879417","https://openalex.org/W2039066264","https://openalex.org/W2117079761","https://openalex.org/W2134797726","https://openalex.org/W2197872593","https://openalex.org/W2269516007","https://openalex.org/W2406470551","https://openalex.org/W2547640786","https://openalex.org/W2594348459","https://openalex.org/W2744643661","https://openalex.org/W2911964244","https://openalex.org/W3120740533","https://openalex.org/W4301347335"],"related_works":["https://openalex.org/W4366990902","https://openalex.org/W3171520305","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487","https://openalex.org/W2591672004","https://openalex.org/W1982169401","https://openalex.org/W2356463514","https://openalex.org/W4319437832"],"abstract_inverted_index":{"To":[0],"learn":[1],"decision":[2,20,34,69],"trees":[3,35],"from":[4,48],"uncertain":[5,26],"data":[6,75],"modelled":[7],"by":[8,45,58],"mass":[9],"functions,":[10],"the":[11,49,53,63,90],"random":[12,46],"training":[13,27],"set":[14,43],"sampling":[15,47],"approach":[16],"for":[17,67,79],"learning":[18],"belief":[19,33,68],"forests":[21],"is":[22,56],"proposed.":[23],"Given":[24],"an":[25,94],"set,":[28],"a":[29],"collection":[30],"of":[31,65,88],"simple":[32],"are":[36,76],"trained":[37],"separately":[38],"on":[39,72,78],"each":[40],"corresponding":[41],"new":[42],"drawn":[44],"original":[50],"one.":[51],"Then":[52],"final":[54],"prediction":[55],"made":[57],"majority":[59],"voting.":[60],"After":[61],"discussing":[62],"selection":[64],"parameters":[66],"forests,":[70],"experiments":[71],"Balance":[73],"scale":[74],"carried":[77],"performance":[80],"validation.":[81],"Results":[82],"show":[83],"that":[84],"with":[85],"different":[86],"kinds":[87],"uncertainty,":[89],"proposed":[91],"method":[92],"guarantees":[93],"obvious":[95],"improvement":[96],"in":[97],"classification":[98],"accuracy.":[99]},"counts_by_year":[{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
