{"id":"https://openalex.org/W99850445","doi":null,"title":"Interaction of Feature Selection Methods and Linear Classification Models","display_name":"Interaction of Feature Selection Methods and Linear Classification Models","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W99850445","mag":"99850445"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.20.6031","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.6031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-ai.ijs.si/DunjaMladenic/TextML02/papers/Brank.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5013478323","display_name":"Janez Brank","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Janez Brank","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043874320","display_name":"Marko Grobelnik","orcid":"https://orcid.org/0000-0001-7373-5591","observed_orcids":["https://orcid.org/0000-0001-7373-5591"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marko Grobelnik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113653594","display_name":"Nata\u0161a Mili\u0107-Frayling","orcid":"https://orcid.org/0000-0003-1244-1973","observed_orcids":["https://orcid.org/0000-0003-1244-1973"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Natasa Milic-Frayling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063095022","display_name":"Dunja Mladeni\u0107","orcid":"https://orcid.org/0000-0002-0360-6505","observed_orcids":["https://orcid.org/0000-0002-0360-6505","https://orcid.org/0000-0003-4480-082X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dunja Mladenic","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7045,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.92902501,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9990000128746033,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9990000128746033,"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/T10028","display_name":"Topic Modeling","score":9.999999747378752e-05,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":9.999999747378752e-05,"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/feature-selection","display_name":"feature selection","score":0.996999979019165},{"id":"https://openalex.org/keywords/linear-classifiers","display_name":"linear classifiers","score":0.7310000061988831},{"id":"https://openalex.org/keywords/document-classification","display_name":"document classification","score":0.9860000014305115},{"id":"https://openalex.org/keywords/two-stage-classification","display_name":"two-stage classification","score":0.414000004529953},{"id":"https://openalex.org/keywords/training-sample-selection","display_name":"training data selection","score":0.5149999856948853}],"concepts":[{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.8082607388496399},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7577290534973145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7119944095611572},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6793195605278015},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6504221558570862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6312777996063232},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.558028519153595},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.49419358372688293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4904765784740448},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4370565414428711},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4265499711036682},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.42212632298469543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3384430408477783}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.20.6031","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.6031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-ai.ijs.si/DunjaMladenic/TextML02/papers/Brank.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1482214997","https://openalex.org/W1507342598","https://openalex.org/W1549887922","https://openalex.org/W1574862351","https://openalex.org/W1604938182","https://openalex.org/W1979367378","https://openalex.org/W2040870580","https://openalex.org/W2054882585","https://openalex.org/W2089933214","https://openalex.org/W2098475626"],"related_works":["https://openalex.org/W2784182661","https://openalex.org/W7096302865","https://openalex.org/W2140390894","https://openalex.org/W7096002084","https://openalex.org/W2520551047","https://openalex.org/W2289119839","https://openalex.org/W1919046912","https://openalex.org/W8815205","https://openalex.org/W2721271875","https://openalex.org/W2490347236"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"explore":[4],"effects":[5],"of":[6],"various":[7],"feature":[8,28,35],"selection":[9,29],"algorithms":[10],"on":[11],"document":[12],"classification":[13],"performance.":[14],"We":[15],"propose":[16],"to":[17,32],"use":[18],"two,":[19],"possibly":[20,43],"distinct":[21],"linear":[22],"classifiers:":[23],"one":[24],"used":[25],"exclusively":[26],"for":[27,37],"in":[30],"order":[31],"obtain":[33],"the":[34,39],"space":[36],"training":[38,46],"second":[40],"classifier,":[41],"using":[42],"a":[44],"different":[45],"set.":[47]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2025-10-27T00:00:00"}