{"id":"https://openalex.org/W4387543528","doi":"https://doi.org/10.1145/3616195.3616217","title":"An Empirical Study on the Effectiveness of Feature Selection and Ensemble Learning Techniques for Music Genre Classification","display_name":"An Empirical Study on the Effectiveness of Feature Selection and Ensemble Learning Techniques for Music Genre Classification","publication_year":2023,"publication_date":"2023-08-30","ids":{"openalex":"https://openalex.org/W4387543528","doi":"https://doi.org/10.1145/3616195.3616217"},"language":"en","primary_location":{"id":"doi:10.1145/3616195.3616217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616195.3616217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616195.3616217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th International Audio Mostly Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3616195.3616217","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021553573","display_name":"Raad Shariat","orcid":"https://orcid.org/0000-0001-5735-975X"},"institutions":[{"id":"https://openalex.org/I107949126","display_name":"University of Lethbridge","ror":"https://ror.org/044j76961","country_code":"CA","type":"education","lineage":["https://openalex.org/I107949126"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Raad Shariat","raw_affiliation_strings":["Department of Mathematics and Computer Science, University of Lethbridge, Canada"],"raw_orcid":"https://orcid.org/0000-0001-5735-975X","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, University of Lethbridge, Canada","institution_ids":["https://openalex.org/I107949126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035284763","display_name":"John Z. Zhang","orcid":"https://orcid.org/0009-0002-1094-0859"},"institutions":[{"id":"https://openalex.org/I107949126","display_name":"University of Lethbridge","ror":"https://ror.org/044j76961","country_code":"CA","type":"education","lineage":["https://openalex.org/I107949126"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"John Zhang","raw_affiliation_strings":["Department of Mathematics and Computer Science, University of Lethbridge, Canada"],"raw_orcid":"https://orcid.org/0009-0002-1094-0859","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, University of Lethbridge, Canada","institution_ids":["https://openalex.org/I107949126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I107949126"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11349","display_name":"Music Technology and Sound Studies","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10788","display_name":"Neuroscience and Music Perception","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8166936635971069},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7670309543609619},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6974706649780273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.673831045627594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6650658249855042},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5614930987358093},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5327486991882324},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5223599672317505},{"id":"https://openalex.org/keywords/music-information-retrieval","display_name":"Music information retrieval","score":0.5162732601165771},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48749423027038574},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4494171738624573},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42546790838241577},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35336393117904663},{"id":"https://openalex.org/keywords/musical","display_name":"Musical","score":0.2279159128665924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8166936635971069},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7670309543609619},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6974706649780273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.673831045627594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6650658249855042},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5614930987358093},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5327486991882324},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5223599672317505},{"id":"https://openalex.org/C2777946086","wikidata":"https://www.wikidata.org/wiki/Q1163335","display_name":"Music information retrieval","level":3,"score":0.5162732601165771},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48749423027038574},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4494171738624573},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42546790838241577},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35336393117904663},{"id":"https://openalex.org/C558565934","wikidata":"https://www.wikidata.org/wiki/Q2743","display_name":"Musical","level":2,"score":0.2279159128665924},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3616195.3616217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616195.3616217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616195.3616217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th International Audio Mostly Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3616195.3616217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616195.3616217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616195.3616217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th International Audio Mostly Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387543528.pdf"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1508363294","https://openalex.org/W2008056655","https://openalex.org/W2017550080","https://openalex.org/W2070462330","https://openalex.org/W2078120539","https://openalex.org/W2088252378","https://openalex.org/W2091085232","https://openalex.org/W2099760476","https://openalex.org/W2100700860","https://openalex.org/W2105114356","https://openalex.org/W2124622020","https://openalex.org/W2125283600","https://openalex.org/W2146434609","https://openalex.org/W2228467293","https://openalex.org/W2312288779","https://openalex.org/W2514413323","https://openalex.org/W2612138235","https://openalex.org/W2768348081","https://openalex.org/W2781947228","https://openalex.org/W2789758093","https://openalex.org/W2793881638","https://openalex.org/W2906214917","https://openalex.org/W3008214279","https://openalex.org/W3083141895","https://openalex.org/W3152939161","https://openalex.org/W4221129010","https://openalex.org/W4285142189","https://openalex.org/W4292622404","https://openalex.org/W4312303369"],"related_works":["https://openalex.org/W3034338377","https://openalex.org/W2373792516","https://openalex.org/W2380784125","https://openalex.org/W2364654346","https://openalex.org/W2538183362","https://openalex.org/W2369033652","https://openalex.org/W3004057759","https://openalex.org/W2889085215","https://openalex.org/W2914806737","https://openalex.org/W2309093070"],"abstract_inverted_index":{"Classical":[0],"machine":[1],"learning":[2,55,124,189],"has":[3],"long":[4],"been":[5],"utilized":[6],"for":[7,126,173],"classification":[8,59,155,177,202],"and":[9,71,81,85,96,113,154,166,183,191],"regression":[10],"tasks,":[11],"primarily":[12],"focusing":[13],"on":[14,69],"tabular":[15],"data":[16,23],"or":[17],"handcrafted":[18],"features":[19,105],"derived":[20],"from":[21,107],"various":[22],"modalities,":[24],"such":[25,92],"as":[26,93],"music":[27,175],"signals.":[28],"Music":[29],"Information":[30],"Retrieval":[31],"(MIR)":[32],"is":[33],"an":[34],"emerging":[35],"field":[36],"that":[37,134],"seeks":[38],"to":[39,57,197],"automate":[40],"the":[41,50,63,99,131,157,180],"management":[42],"process":[43],"of":[44,52,65,164,185,199],"musical":[45,90,200],"data.":[46],"This":[47,169],"paper":[48],"explores":[49],"potential":[51],"employing":[53,122],"ensemble":[54,123,188],"techniques":[56,125],"enhance":[58],"performance":[60,119,158],"while":[61,98],"assessing":[62],"impact":[64],"feature":[66,137,152,192],"selection":[67,138,153,182,193],"methods":[68,139],"accuracy":[70,165],"computational":[72,143,167],"efficiency":[73],"across":[74],"three":[75],"publicly":[76],"available":[77],"datasets:":[78],"Spotify,":[79],"TCC_CED,":[80],"GTZAN.":[82],"The":[83,110],"Spotify":[84],"TCC_CED":[86],"datasets":[87],"contain":[88],"high-level":[89,128],"features,":[91],"energy,":[94],"key,":[95],"duration,":[97],"GTZAN":[100],"dataset":[101],"incorporates":[102],"low-level":[103],"acoustic":[104],"extracted":[106],"audio":[108],"recordings.":[109],"empirical":[111],"experiments":[112],"qualitative":[114],"analysis":[115],"reveal":[116],"a":[117,146],"significant":[118],"improvement":[120],"when":[121],"handling":[127],"features.":[129],"Furthermore,":[130],"findings":[132],"suggest":[133],"applying":[135],"appropriate":[136],"can":[140,159],"substantially":[141],"reduce":[142],"time.":[144,168],"As":[145],"result,":[147],"by":[148],"strategically":[149],"combining":[150],"optimal":[151],"models,":[156],"be":[160],"boosted":[161],"in":[162,204],"terms":[163],"study":[170],"provides":[171],"insights":[172],"optimizing":[174],"genre":[176,201],"tasks":[178,203],"through":[179],"strategic":[181],"balancing":[184],"model":[186],"performance,":[187],"techniques,":[190],"methods,":[194],"ultimately":[195],"contributing":[196],"advancements":[198],"MIR.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}