{"id":"https://openalex.org/W2119892344","doi":"https://doi.org/10.1109/iri.2007.4296675","title":"Using Reconstructability Analysis for Input Variable Reduction: A Business Example","display_name":"Using Reconstructability Analysis for Input Variable Reduction: A Business Example","publication_year":2007,"publication_date":"2007-08-01","ids":{"openalex":"https://openalex.org/W2119892344","doi":"https://doi.org/10.1109/iri.2007.4296675","mag":"2119892344"},"language":"en","primary_location":{"id":"doi:10.1109/iri.2007.4296675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2007.4296675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Information Reuse and Integration","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pdxscholar.library.pdx.edu/sysc_fac/136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065157776","display_name":"Stephen Shervais","orcid":null},"institutions":[{"id":"https://openalex.org/I159107703","display_name":"Eastern Washington University","ror":"https://ror.org/002g57a93","country_code":"US","type":"education","lineage":["https://openalex.org/I159107703"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Shervais","raw_affiliation_strings":["Eastern Washington University, WA, USA","Eastern Washington University, Cheney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eastern Washington University, WA, USA","institution_ids":["https://openalex.org/I159107703"]},{"raw_affiliation_string":"Eastern Washington University, Cheney","institution_ids":["https://openalex.org/I159107703"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038714210","display_name":"Martin Zwick","orcid":"https://orcid.org/0000-0002-7247-6636"},"institutions":[{"id":"https://openalex.org/I126345244","display_name":"Portland State University","ror":"https://ror.org/00yn2fy02","country_code":"US","type":"education","lineage":["https://openalex.org/I126345244"]},{"id":"https://openalex.org/I159107703","display_name":"Eastern Washington University","ror":"https://ror.org/002g57a93","country_code":"US","type":"education","lineage":["https://openalex.org/I159107703"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Zwick","raw_affiliation_strings":["Portland State University, Portland, OR, USA","Eastern Washington University, Cheney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Portland State University, Portland, OR, USA","institution_ids":["https://openalex.org/I126345244"]},{"raw_affiliation_string":"Eastern Washington University, Cheney","institution_ids":["https://openalex.org/I159107703"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13431803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"532","last_page":"537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.978600025177002,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.978600025177002,"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"}},{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.7721809148788452},{"id":"https://openalex.org/keywords/variables","display_name":"Variables","score":0.6434590220451355},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5380690693855286},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.530808687210083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5047513246536255},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46012401580810547},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4194902777671814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3873530626296997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35128000378608704},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32160085439682007}],"concepts":[{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.7721809148788452},{"id":"https://openalex.org/C27574286","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Variables","level":2,"score":0.6434590220451355},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5380690693855286},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.530808687210083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5047513246536255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46012401580810547},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4194902777671814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3873530626296997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35128000378608704},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32160085439682007},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iri.2007.4296675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2007.4296675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Information Reuse and Integration","raw_type":"proceedings-article"},{"id":"pmh:oai:pdxscholar.library.pdx.edu:sysc_fac-1138","is_oa":true,"landing_page_url":"https://pdxscholar.library.pdx.edu/sysc_fac/136","pdf_url":"https://pdxscholar.library.pdx.edu/sysc_fac/136","source":{"id":"https://openalex.org/S4377196300","display_name":"PDXScholar  (Portland State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126345244","host_organization_name":"Portland State University","host_organization_lineage":["https://openalex.org/I126345244"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Systems Science Faculty Publications and Presentations","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.230.6622","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.230.6622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.pdx.edu/sites/www.pdx.edu.sysc/files/sysc_IRI07Proceedings.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:pdxscholar.library.pdx.edu:sysc_fac-1138","is_oa":true,"landing_page_url":"https://pdxscholar.library.pdx.edu/sysc_fac/136","pdf_url":"https://pdxscholar.library.pdx.edu/sysc_fac/136","source":{"id":"https://openalex.org/S4377196300","display_name":"PDXScholar  (Portland State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126345244","host_organization_name":"Portland State University","host_organization_lineage":["https://openalex.org/I126345244"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Systems Science Faculty Publications and Presentations","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2119892344.pdf","grobid_xml":"https://content.openalex.org/works/W2119892344.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W6196333","https://openalex.org/W143088742","https://openalex.org/W199129542","https://openalex.org/W397887861","https://openalex.org/W1838213182","https://openalex.org/W1864615136","https://openalex.org/W2006989378","https://openalex.org/W2084812512","https://openalex.org/W2123630302","https://openalex.org/W2127135920","https://openalex.org/W2140299844","https://openalex.org/W2145535809","https://openalex.org/W2157646585","https://openalex.org/W2168175751","https://openalex.org/W2169747954","https://openalex.org/W2327022120","https://openalex.org/W3087675653","https://openalex.org/W4211153813","https://openalex.org/W6605727443","https://openalex.org/W6613749038","https://openalex.org/W6681654422","https://openalex.org/W6783513180","https://openalex.org/W7074181722"],"related_works":["https://openalex.org/W2397288865","https://openalex.org/W2368524271","https://openalex.org/W2576709312","https://openalex.org/W2079402751","https://openalex.org/W2392797073","https://openalex.org/W2989490741","https://openalex.org/W2023657818","https://openalex.org/W2384907669","https://openalex.org/W4311072340","https://openalex.org/W4375841781"],"abstract_inverted_index":{"We":[0],"demonstrate":[1],"the":[2,9,16,55,85,106,112,131],"use":[3],"of":[4,18,57,66,72,84,101],"reconstructability":[5],"analysis":[6,24],"(RA)":[7],"on":[8],"UCI":[10],"Australian":[11],"Credit":[12],"dataset":[13],"to":[14,36,53,62],"reduce":[15,54],"number":[17,56],"input":[19],"variables":[20,59],"for":[21],"two":[22,63],"different":[23,64],"tools.":[25],"Using":[26],"14":[27,61],"variables,":[28],"an":[29],"artificial":[30],"neural":[31],"net":[32],"(NN)":[33],"is":[34,88,115,128],"able":[35],"predict":[37],"whether":[38],"or":[39],"not":[40,89,116],"credit":[41],"was":[42],"granted,":[43],"with":[44,130],"a":[45,124],"79.1%":[46],"success":[47,70,99],"rate.":[48],"RA":[49,97],"preprocessing":[50],"allows":[51],"us":[52],"independent":[58],"from":[60],"sets":[65],"three,":[67],"which":[68],"have":[69],"rates":[71,81,100],"77.2%":[73],"and":[74,82,103,111],"76.9%":[75],"respectively.":[76],"The":[77,92],"difference":[78,107],"between":[79,108],"these":[80],"that":[83,119,127],"14-variable":[86,113,132],"NN":[87,114],"statistically":[90,117],"significant.":[91],"three-variable":[93,125],"rulesets":[94],"given":[95],"by":[96],"achieve":[98],"77.8%":[102],"79.7%.":[104],"Again,":[105],"those":[109],"values":[110],"significant,":[118],"is,":[120],"our":[121],"approach":[122],"provides":[123],"model":[126],"competitive":[129],"equivalent.":[133]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
