{"id":"https://openalex.org/W4362564585","doi":"https://doi.org/10.1109/assic55218.2022.10088385","title":"An Adaptive Synthetic Sample Coupled With Ensemble Multi-Filter Approaches For The High Dimensional Imbalanced Dataset","display_name":"An Adaptive Synthetic Sample Coupled With Ensemble Multi-Filter Approaches For The High Dimensional Imbalanced Dataset","publication_year":2022,"publication_date":"2022-11-19","ids":{"openalex":"https://openalex.org/W4362564585","doi":"https://doi.org/10.1109/assic55218.2022.10088385"},"language":"en","primary_location":{"id":"doi:10.1109/assic55218.2022.10088385","doi":"https://doi.org/10.1109/assic55218.2022.10088385","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/assic55218.2022.10088385","pdf_url":null,"source":{"id":"https://openalex.org/S7407086684","display_name":"International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5010514435","display_name":"Abdulrauf Garba Sharifai","orcid":"https://orcid.org/0000-0001-7136-8409","observed_orcids":["https://orcid.org/0000-0001-7136-8409"]},"institutions":[{"id":"https://openalex.org/I4210099431","display_name":"Maitama Sule University Kano","ror":"https://ror.org/011wymc20","country_code":"NG","type":"education","lineage":["https://openalex.org/I4210099431"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Abdulrauf Garba Sharifai","raw_affiliation_strings":["Yusuf Maitama Sule University Kano,Department of Computer Science,Kano,Nigeria","Department of Computer Science, Yusuf Maitama Sule University Kano, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yusuf Maitama Sule University Kano,Department of Computer Science,Kano,Nigeria","institution_ids":["https://openalex.org/I4210099431"]},{"raw_affiliation_string":"Department of Computer Science, Yusuf Maitama Sule University Kano, Kano, Nigeria","institution_ids":["https://openalex.org/I4210099431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006001080","display_name":"Ishola Dada Muraina","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210099431","display_name":"Maitama Sule University Kano","ror":"https://ror.org/011wymc20","country_code":"NG","type":"education","lineage":["https://openalex.org/I4210099431"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Ishola Dada Muraina","raw_affiliation_strings":["Yusuf Maitama Sule University Kano,Department of Computer Science,Kano,Nigeria","Department of Computer Science, Yusuf Maitama Sule University Kano, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yusuf Maitama Sule University Kano,Department of Computer Science,Kano,Nigeria","institution_ids":["https://openalex.org/I4210099431"]},{"raw_affiliation_string":"Department of Computer Science, Yusuf Maitama Sule University Kano, Kano, Nigeria","institution_ids":["https://openalex.org/I4210099431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089104578","display_name":"Usman Alhaji Abdurrahman","orcid":"https://orcid.org/0000-0002-5315-0219","observed_orcids":["https://orcid.org/0000-0002-5315-0219"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Usman Alhaji Abdurrahman","raw_affiliation_strings":["School of Information Science and Technology Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.35,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81958102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.5220000147819519,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.5220000147819519,"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"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.47530001401901245,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0003000000142492354,"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/imbalanced-learning","display_name":"imbalanced learning","score":0.7170000076293945},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.9430000185966492},{"id":"https://openalex.org/keywords/adasyn","display_name":"ADASYN","score":0.828000009059906},{"id":"https://openalex.org/keywords/synthetic-minority-samples","display_name":"synthetic minority samples","score":0.6430000066757202},{"id":"https://openalex.org/keywords/gene-selection","display_name":"gene selection","score":0.6389999985694885},{"id":"https://openalex.org/keywords/biomarker-genes","display_name":"biomarker genes","score":0.7749999761581421},{"id":"https://openalex.org/keywords/dna-microarrays","display_name":"DNA microarrays","score":0.7889999747276306},{"id":"https://openalex.org/keywords/cancer-diagnosis","display_name":"cancer diagnosis","score":0.7519999742507935},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.6010000109672546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520053386688232},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6029722094535828},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5351427793502808},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5323097705841064},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5231860280036926},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49874401092529297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47190433740615845},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46425965428352356},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.45022767782211304},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11827853322029114},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.07709905505180359},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/assic55218.2022.10088385","doi":"https://doi.org/10.1109/assic55218.2022.10088385","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/assic55218.2022.10088385","pdf_url":null,"source":{"id":"https://openalex.org/S7407086684","display_name":"International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W167016754","https://openalex.org/W1493357981","https://openalex.org/W1500690868","https://openalex.org/W1504974927","https://openalex.org/W1563938718","https://openalex.org/W1685464609","https://openalex.org/W1692174238","https://openalex.org/W1936399835","https://openalex.org/W2000621750","https://openalex.org/W2006825483","https://openalex.org/W2019858993","https://openalex.org/W2032867948","https://openalex.org/W2040010062","https://openalex.org/W2099550922","https://openalex.org/W2104167780","https://openalex.org/W2104933073","https://openalex.org/W2107335650","https://openalex.org/W2109826612","https://openalex.org/W2110883665","https://openalex.org/W2119191234","https://openalex.org/W2119387367","https://openalex.org/W2120040939","https://openalex.org/W2128965734","https://openalex.org/W2138776277","https://openalex.org/W2139986471","https://openalex.org/W2148143831","https://openalex.org/W2154706222","https://openalex.org/W2171141701","https://openalex.org/W2190423096","https://openalex.org/W2309023520","https://openalex.org/W2377310215","https://openalex.org/W2396908641","https://openalex.org/W2404077489","https://openalex.org/W2476684388","https://openalex.org/W2536062280","https://openalex.org/W2540352327","https://openalex.org/W2606690353","https://openalex.org/W2740808776","https://openalex.org/W2772077888","https://openalex.org/W2811460725","https://openalex.org/W2911966664","https://openalex.org/W2933246980","https://openalex.org/W2948676369","https://openalex.org/W2950458545","https://openalex.org/W2963181848","https://openalex.org/W3128571949","https://openalex.org/W3133679465","https://openalex.org/W4226052951","https://openalex.org/W4285743491","https://openalex.org/W4309118588","https://openalex.org/W6742005128"],"related_works":["https://openalex.org/W4281386999","https://openalex.org/W2919755861","https://openalex.org/W4393278006","https://openalex.org/W2104933073","https://openalex.org/W2899864072","https://openalex.org/W3014181473","https://openalex.org/W4390732527","https://openalex.org/W2618978649","https://openalex.org/W4409356956","https://openalex.org/W2336074659"],"abstract_inverted_index":{"DNA":[0,143],"microarray":[1,144],"dataset":[2,37],"infamously":[3],"comprises":[4],"a":[5,39,51,72,160],"high":[6,47,86,98],"dimensional":[7,48,87,99],"and":[8,27,42],"class":[9,35],"imbalanced":[10,88,100,109,170],"dataset,":[11],"these":[12,61],"problems":[13,95],"pose":[14],"severe":[15],"challenges":[16],"for":[17,24,84,107,120],"the":[18,34,85,94,97,108,117,124,135,148,152,166],"accurate":[19],"identification":[20],"of":[21,54,75,96,168],"biomarker":[22],"genes":[23],"cancer":[25],"diagnosis":[26],"classification.":[28],"The":[29],"training":[30],"learning":[31,110],"model":[32],"on":[33,141],"imbalance":[36],"is":[38,113,131,158],"challenging":[40],"task":[41],"became":[43],"more":[44],"tedious":[45],"with":[46,81,128],"features.":[49],"However,":[50],"small":[52],"number":[53],"techniques":[55],"have":[56],"been":[57],"proposed":[58,149],"to":[59,65,92,115,133],"address":[60],"issues":[62],"simultaneously":[63],"due":[64],"their":[66],"complicated":[67],"intersection.":[68],"This":[69],"paper":[70],"proposes":[71],"hybrid":[73],"approach":[74,106,150],"an":[76],"adaptive":[77,103],"synthetic":[78,104,118],"sampling":[79,105],"coupled":[80],"ensemble":[82,125],"multi-filter":[83,126],"datasets":[89,145],"(ADASYN-EMF)":[90],"method":[91,112],"overcome":[93],"datasets.":[101,171],"An":[102],"(ADASYN)":[111],"used":[114],"generate":[116],"examples":[119],"positive":[121],"class,":[122],"while":[123],"combined":[127],"Correlation-Based":[129],"Redundancy":[130],"utilized":[132],"select":[134],"most":[136],"robust":[137,161],"gene":[138],"subsets.":[139],"Experiments":[140],"five":[142],"reveal":[146],"that":[147,163],"outperforms":[151],"state":[153],"art":[154],"methods.":[155],"Thus,":[156],"ADASYN-EMF":[157],"considered":[159],"technique":[162],"can":[164],"handle":[165],"problem":[167],"high-dimensional":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2023-04-06T00:00:00"}