{"id":"https://openalex.org/W2155248182","doi":"https://doi.org/10.1109/icmlc.2011.6016813","title":"A comparative study among different kernel functions in flexible naïve Bayesian classification","display_name":"A comparative study among different kernel functions in flexible naïve Bayesian classification","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2155248182","doi":"https://doi.org/10.1109/icmlc.2011.6016813","mag":"2155248182"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2011.6016813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2011.6016813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Machine Learning and Cybernetics","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":null,"display_name":"James N. K. Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"James N. K. Liu","raw_affiliation_strings":["Department of computing, Hong Kong Polytechnic University, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of computing, Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076542236","display_name":"Yulin He","orcid":"https://orcid.org/0000-0002-3415-0686"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Lin He","raw_affiliation_strings":["Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding, China"],"affiliations":[{"raw_affiliation_string":"Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073006299","display_name":"Xizhao Wang","orcid":"https://orcid.org/0000-0001-6036-4728"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi-Zhao Wang","raw_affiliation_strings":["Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding, China"],"affiliations":[{"raw_affiliation_string":"Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101190299","display_name":"Yanxing Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yan-Xing Hu","raw_affiliation_strings":["Department of computing, Hong Kong Polytechnic University, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of computing, Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":1.7539,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87701634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"4304","issue":null,"first_page":"638","last_page":"643"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9977999925613403,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9977999925613403,"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":0.9955000281333923,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6199181079864502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.605368971824646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5970603227615356},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5835276246070862},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5692000985145569},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5165364146232605},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4874577522277832},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44690439105033875},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4214504361152649},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36313527822494507},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33787935972213745}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6199181079864502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605368971824646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5970603227615356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5835276246070862},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5692000985145569},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5165364146232605},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4874577522277832},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44690439105033875},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4214504361152649},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36313527822494507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33787935972213745},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icmlc.2011.6016813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2011.6016813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/12177","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/12177","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322598","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W172260869","https://openalex.org/W1912123407","https://openalex.org/W1912982817","https://openalex.org/W1974758710","https://openalex.org/W1975446127","https://openalex.org/W2063637550","https://openalex.org/W2093040750","https://openalex.org/W2118020555","https://openalex.org/W2137587467","https://openalex.org/W3120740533","https://openalex.org/W4238717354","https://openalex.org/W6640114639","https://openalex.org/W6788247690"],"related_works":["https://openalex.org/W4220715471","https://openalex.org/W4295035285","https://openalex.org/W2019890371","https://openalex.org/W4200022986","https://openalex.org/W2963637926","https://openalex.org/W3130734945","https://openalex.org/W2048140462","https://openalex.org/W4388542635","https://openalex.org/W2380827615","https://openalex.org/W2122582912"],"abstract_inverted_index":{"When":[0],"determining":[1],"the":[2,5,17,22,29,40,49,64,88,92,98,108,111,116,136,140,149,158,166,168,176,181,188],"class":[3,18,99],"of":[4,42,70],"unknown":[6],"example":[7],"by":[8,107],"using":[9,139],"na\u00efve":[10,66],"Bayesian":[11,27],"classifier,":[12,28],"we":[13],"need":[14],"to":[15,87],"estimate":[16],"conditional":[19,117],"probabilities":[20],"for":[21,36],"continuous":[23],"attributes.":[24],"In":[25,46],"flexible":[26,65],"Gaussian":[30,153,169],"kernel":[31,52,154,170],"function":[32],"is":[33,171],"frequently":[34],"used":[35,152],"classification":[37,93,160],"task":[38],"under":[39,110],"framework":[41],"Parzen":[43],"window":[44],"method.":[45],"this":[47],"paper,":[48],"other":[50,177],"six":[51,178],"functions":[53],"(uniform,":[54],"triangular,":[55],"epanechnikov,":[56],"biweight,":[57],"triweight":[58],"and":[59,97,115,135,162],"cosine)":[60],"are":[61,74,83,105,124,184],"introduced":[62],"in":[63,76],"Bayesian.":[67],"The":[68,80,102,121,144],"performances":[69],"these":[71],"seven":[72],"kernels":[73,123],"compared":[75,125],"30":[77],"UCI":[78],"datasets.":[79],"experimental":[81,145,189],"comparisons":[82],"carried":[84],"out":[85],"according":[86],"following":[89],"three":[90],"aspects:":[91],"accuracy,":[94],"ranking":[95],"performance":[96],"probability":[100],"estimation.":[101],"latter":[103],"two":[104],"measured":[106],"area":[109],"ROC":[112],"curve":[113],"(AUC)":[114],"log":[118],"likelihood":[119],"(CLL).":[120],"related":[122],"via":[126],"two-tailed":[127],"t-test":[128],"with":[129],"a":[130],"95":[131],"percent":[132],"confidence":[133],"level":[134],"Friedman's":[137],"test":[138],"0.05":[141],"critical":[142],"level.":[143],"results":[146],"show":[147],"that":[148],"most":[150],"commonly":[151],"can":[155],"not":[156],"achieve":[157],"best":[159],"accuracy":[161],"AUC.":[163],"However,":[164],"on":[165,187],"CLL,":[167],"statistically":[172],"significantly":[173],"better":[174],"than":[175],"kernels.":[179],"Finally,":[180],"corresponding":[182],"analyses":[183],"given":[185],"based":[186],"results.":[190]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}