{"id":"https://openalex.org/W2115971619","doi":"https://doi.org/10.1109/enc.2009.23","title":"Meaningful Error Estimations for Data Analysis","display_name":"Meaningful Error Estimations for Data Analysis","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W2115971619","doi":"https://doi.org/10.1109/enc.2009.23","mag":"2115971619"},"language":"en","primary_location":{"id":"doi:10.1109/enc.2009.23","is_oa":false,"landing_page_url":"https://doi.org/10.1109/enc.2009.23","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Mexican International Conference on Computer Science","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":"https://openalex.org/A5064309434","display_name":"Ren\u00e9 Villeda-Ruz","orcid":null},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Ren\u00e9 Villeda-Ruz","raw_affiliation_strings":["Facultad de Ciencias, UNAM, Mexico, Mexico","Fac. de Cienc., U.N.A.M, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Facultad de Ciencias, UNAM, Mexico, Mexico","institution_ids":["https://openalex.org/I8961855"]},{"raw_affiliation_string":"Fac. de Cienc., U.N.A.M, Mexico City, Mexico","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038679061","display_name":"Javier Garc\u0131\u0301a-Garc\u0131\u0301a","orcid":"https://orcid.org/0000-0001-9539-2606"},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Javier Garcia-Garcia","raw_affiliation_strings":["Facultad de Ciencias, UNAM, Mexico, Mexico","Fac. de Cienc., U.N.A.M, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Facultad de Ciencias, UNAM, Mexico, Mexico","institution_ids":["https://openalex.org/I8961855"]},{"raw_affiliation_string":"Fac. de Cienc., U.N.A.M, Mexico City, Mexico","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064309434"],"corresponding_institution_ids":["https://openalex.org/I8961855"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11974676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"280","last_page":"288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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/T11652","display_name":"Imbalanced Data Classification Techniques","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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8106176853179932},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5978389978408813},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5972780585289001},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.589144229888916},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.572274386882782},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5458460450172424},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5352352857589722},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45660972595214844},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16854050755500793}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8106176853179932},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5978389978408813},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5972780585289001},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.589144229888916},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.572274386882782},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5458460450172424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5352352857589722},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45660972595214844},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16854050755500793},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/enc.2009.23","is_oa":false,"landing_page_url":"https://doi.org/10.1109/enc.2009.23","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Mexican International Conference on Computer Science","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321739","display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","ror":"https://ror.org/059ex5q34"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W177590838","https://openalex.org/W342038080","https://openalex.org/W1506073843","https://openalex.org/W1527889912","https://openalex.org/W1530010412","https://openalex.org/W1550206324","https://openalex.org/W1551385575","https://openalex.org/W1552511023","https://openalex.org/W1565201084","https://openalex.org/W1625504505","https://openalex.org/W1680392829","https://openalex.org/W2084134149","https://openalex.org/W2113131266","https://openalex.org/W2135863341","https://openalex.org/W2140190241","https://openalex.org/W2142334564","https://openalex.org/W2168754135","https://openalex.org/W2995425287","https://openalex.org/W3017143921","https://openalex.org/W4212848460","https://openalex.org/W6607301666","https://openalex.org/W6611507263","https://openalex.org/W6630364308","https://openalex.org/W6631626606","https://openalex.org/W6632865047","https://openalex.org/W6632945054","https://openalex.org/W6633798749","https://openalex.org/W6636859864","https://openalex.org/W6637170354","https://openalex.org/W6637386731","https://openalex.org/W6680704940","https://openalex.org/W6738852829","https://openalex.org/W6776565550"],"related_works":["https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2726838704","https://openalex.org/W4220802396","https://openalex.org/W2393473353","https://openalex.org/W2373790322","https://openalex.org/W1989494794","https://openalex.org/W2122031327","https://openalex.org/W1184238669","https://openalex.org/W3032901101"],"abstract_inverted_index":{"Much":[0],"work":[1],"has":[2],"been":[3],"done":[4],"in":[5,15,21,47,88,153],"recent":[6],"years":[7],"on":[8],"designing":[9],"techniques":[10,35],"used":[11,109],"as":[12,110],"support":[13],"tools":[14],"the":[16,31,43,52,65,84,103,122,127,134,137,154],"knowledge":[17,67,156],"discovery":[18,68,157],"process,":[19],"particularly":[20],"classification":[22],"tasks.":[23],"In":[24,70],"most":[25],"cases":[26],"it":[27,116],"is":[28,38,117],"assumed":[29],"that":[30,91,129],"data":[32,44,53,123,128],"where":[33],"these":[34],"are":[36,149],"applied":[37],"free":[39],"of":[40,60,86,97,143],"errors":[41,87],"or":[42],"was":[45],"cleaned":[46],"a":[48,57,79,89,111,141,150],"previous":[49],"phase.":[50],"However":[51],"cleaning":[54,124,138],"process":[55,139],"represents":[56],"great":[58],"amount":[59,85],"time":[61,144],"and":[62,145],"effort":[63,146],"to":[64,77,81,113,119],"general":[66],"process.":[69,158],"this":[71],"paper,":[72],"we":[73],"present":[74],"preliminary":[75],"results":[76,106,148],"devise":[78],"method":[80],"determine":[82,114],"if":[83,115],"dataset":[90],"will":[92,101,130],"be":[93,108,131],"processed":[94,132],"by":[95,133],"means":[96],"Naive":[98],"Bayes":[99],"classifier":[100],"influence":[102],"results.":[104],"Our":[105],"may":[107],"criterion":[112],"necessary":[118],"carry":[120],"out":[121],"tasks":[125],"over":[126],"classifier.":[135],"Since":[136],"takes":[140],"lot":[142],"our":[147],"helpful":[151],"tool":[152],"overall":[155]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}