{"id":"https://openalex.org/W2408537181","doi":"https://doi.org/10.5220/0004759503500357","title":"Learning on Vertically Partitioned Data based on Chi-square Feature Selection and Naive Bayes Classification","display_name":"Learning on Vertically Partitioned Data based on Chi-square Feature Selection and Naive Bayes Classification","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2408537181","doi":"https://doi.org/10.5220/0004759503500357","mag":"2408537181"},"language":"en","primary_location":{"id":"doi:10.5220/0004759503500357","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004759503500357","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0004759503500357","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042436168","display_name":"Ver\u00f3nica Bol\u00f3n\u2010Canedo","orcid":"https://orcid.org/0000-0002-0524-6427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ver\u00f3nica Bol\u00f3n-Canedo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051434163","display_name":"Diego Peteiro-Barral","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Diego Peteiro-Barral","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048207145","display_name":"Amparo Alonso\u2010Betanzos","orcid":"https://orcid.org/0000-0003-0950-0012"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amparo Alonso-Betanzos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046448840","display_name":"Bertha Guijarro\u2010Berdi\u00f1as","orcid":"https://orcid.org/0000-0001-8901-5441"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bertha Guijarro-Berdi\u00f1as","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083520153","display_name":"Noelia S\u00e1nchez\u2010Maro\u00f1o","orcid":"https://orcid.org/0000-0003-4025-1405"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Noelia S\u00e1nchez-Maro\u00f1o","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.27709273,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"350","last_page":"357"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9897000193595886,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9897000193595886,"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/T12676","display_name":"Machine Learning and ELM","score":0.919700026512146,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9162999987602234,"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/computer-science","display_name":"Computer science","score":0.7945842742919922},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7785312533378601},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6571371555328369},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5850840210914612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5831766724586487},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5665478706359863},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5183330774307251},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4843691289424896},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47881513833999634},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.46405115723609924},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.44202932715415955},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.41200077533721924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3811262249946594},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1117977499961853}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7945842742919922},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7785312533378601},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6571371555328369},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5850840210914612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5831766724586487},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5665478706359863},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5183330774307251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4843691289424896},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47881513833999634},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.46405115723609924},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.44202932715415955},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.41200077533721924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3811262249946594},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1117977499961853},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004759503500357","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004759503500357","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0004759503500357","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004759503500357","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2374047926","https://openalex.org/W2394466068","https://openalex.org/W2381401419","https://openalex.org/W2383501440","https://openalex.org/W4312866165","https://openalex.org/W2957157835","https://openalex.org/W145653800","https://openalex.org/W83434975","https://openalex.org/W2393473353","https://openalex.org/W3153505674"],"abstract_inverted_index":{"In":[0,51],"the":[1,9,16,29,46,75,82,86,103,119,126,132],"last":[2],"few":[3],"years,":[4],"distributed":[5,24],"learning":[6,58],"has":[7],"been":[8],"focus":[10],"of":[11,18,32,134],"much":[12],"attention":[13],"due":[14],"to":[15,90],"explosion":[17],"big":[19],"databases,":[20],"in":[21,106],"some":[22],"cases":[23],"across":[25],"different":[26],"nodes.":[27],"However,":[28],"great":[30],"majority":[31],"current":[33],"selection":[34,69],"and":[35,70,79,85],"classification":[36,127],"algorithms":[37],"are":[38],"designed":[39],"for":[40,57],"centralized":[41],"learning,":[42],"i.e.":[43],"they":[44],"use":[45],"whole":[47],"dataset":[48],"at":[49,92],"once.":[50],"this":[52],"paper,":[53],"a":[54,96],"new":[55],"approach":[56,73],"on":[59,113],"vertically":[60],"partitioned":[61],"data":[62,76],"is":[63,99,122,129],"presented,":[64],"which":[65,101],"covers":[66],"both":[67],"feature":[68],"classification.":[71],"The":[72,110],"splits":[74],"by":[77],"features,":[78],"then":[80],"uses":[81],"chi-square":[83],"filter":[84],"naive":[87],"Bayes":[88],"classifier":[89],"learn":[91],"each":[93],"node.":[94],"Finally,":[95],"merging":[97],"procedure":[98],"performed,":[100],"updates":[102],"learned":[104],"model":[105],"an":[107],"incremental":[108],"fashion.":[109],"experimental":[111],"results":[112],"five":[114],"representative":[115],"datasets":[116],"show":[117],"that":[118],"execution":[120],"time":[121],"shortened":[123],"considerably":[124],"whereas":[125],"performance":[128],"maintained":[130],"as":[131],"number":[133],"nodes":[135],"increases.":[136]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2016-06-24T00:00:00"}