{"id":"https://openalex.org/W4411204623","doi":"https://doi.org/10.3390/info16060486","title":"The Interpretative Effects of Normalization Techniques on Complex Regression Modeling: An Application to Real Estate Values Using Machine Learning","display_name":"The Interpretative Effects of Normalization Techniques on Complex Regression Modeling: An Application to Real Estate Values Using Machine Learning","publication_year":2025,"publication_date":"2025-06-11","ids":{"openalex":"https://openalex.org/W4411204623","doi":"https://doi.org/10.3390/info16060486"},"language":"en","primary_location":{"id":"doi:10.3390/info16060486","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16060486","pdf_url":"https://www.mdpi.com/2078-2489/16/6/486/pdf?version=1749709176","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/6/486/pdf?version=1749709176","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021817994","display_name":"Debora Anelli","orcid":"https://orcid.org/0000-0001-6235-3440"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Debora Anelli","raw_affiliation_strings":["Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0001-6235-3440","affiliations":[{"raw_affiliation_string":"Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040021511","display_name":"Pierluigi Morano","orcid":"https://orcid.org/0000-0001-8049-1206"},"institutions":[{"id":"https://openalex.org/I68618741","display_name":"Polytechnic University of Bari","ror":"https://ror.org/03c44v465","country_code":"IT","type":"education","lineage":["https://openalex.org/I68618741"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pierluigi Morano","raw_affiliation_strings":["Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, 70126 Bari, Italy"],"raw_orcid":"https://orcid.org/0000-0001-8049-1206","affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, 70126 Bari, Italy","institution_ids":["https://openalex.org/I68618741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024074870","display_name":"Francesco Tajani","orcid":"https://orcid.org/0000-0002-2011-1950"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Tajani","raw_affiliation_strings":["Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-2011-1950","affiliations":[{"raw_affiliation_string":"Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080732164","display_name":"Maria Rosaria Guarini","orcid":"https://orcid.org/0000-0002-8675-7498"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maria Rosaria Guarini","raw_affiliation_strings":["Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-8675-7498","affiliations":[{"raw_affiliation_string":"Department of Architecture and Design, \u201cSapienza\u201d University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Architecture and Design, \"Sapienza\" University of Rome, 00196 Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021817994"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":6.6762,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.96538294,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"16","issue":"6","first_page":"486","last_page":"486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.838100016117096,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.838100016117096,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10632","display_name":"Housing Market and Economics","score":0.8119999766349792,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.7178999781608582,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7988975644111633},{"id":"https://openalex.org/keywords/real-estate","display_name":"Real estate","score":0.5111930966377258},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4887208938598633},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.480699360370636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4663034677505493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4531335234642029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3808201253414154},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3807034194469452},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2898537814617157},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26471370458602905},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.13375967741012573},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.12932142615318298},{"id":"https://openalex.org/keywords/social-science","display_name":"Social science","score":0.07036074995994568}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7988975644111633},{"id":"https://openalex.org/C82279013","wikidata":"https://www.wikidata.org/wiki/Q684740","display_name":"Real estate","level":2,"score":0.5111930966377258},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4887208938598633},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.480699360370636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4663034677505493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4531335234642029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3808201253414154},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3807034194469452},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2898537814617157},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26471370458602905},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.13375967741012573},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.12932142615318298},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.07036074995994568},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info16060486","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16060486","pdf_url":"https://www.mdpi.com/2078-2489/16/6/486/pdf?version=1749709176","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cc234e02b59b4e7a88b16757da5601d3","is_oa":true,"landing_page_url":"https://doaj.org/article/cc234e02b59b4e7a88b16757da5601d3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 6, p 486 (2025)","raw_type":"article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1751997","is_oa":false,"landing_page_url":"https://hdl.handle.net/11573/1751997","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3390/info16060486","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16060486","pdf_url":"https://www.mdpi.com/2078-2489/16/6/486/pdf?version=1749709176","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411204623.pdf","grobid_xml":"https://content.openalex.org/works/W4411204623.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1515084353","https://openalex.org/W1836465849","https://openalex.org/W1961147827","https://openalex.org/W2082642737","https://openalex.org/W2130765775","https://openalex.org/W2161336914","https://openalex.org/W2735324362","https://openalex.org/W2768055745","https://openalex.org/W2770558473","https://openalex.org/W2886188206","https://openalex.org/W3019435264","https://openalex.org/W3022013310","https://openalex.org/W3089899327","https://openalex.org/W3092248103","https://openalex.org/W3136643612","https://openalex.org/W3154417060","https://openalex.org/W3205049624","https://openalex.org/W4200072809","https://openalex.org/W4200385155","https://openalex.org/W4214532404","https://openalex.org/W4244628426","https://openalex.org/W4256669726","https://openalex.org/W4283806544","https://openalex.org/W4287660544","https://openalex.org/W4292857100","https://openalex.org/W4311543603","https://openalex.org/W4312590014","https://openalex.org/W4312803182","https://openalex.org/W4313176073","https://openalex.org/W4320730385","https://openalex.org/W4323317853","https://openalex.org/W4386281023","https://openalex.org/W4389206692","https://openalex.org/W4391026828","https://openalex.org/W4402100671","https://openalex.org/W4403190080","https://openalex.org/W4403668631","https://openalex.org/W4406664508","https://openalex.org/W6641082943","https://openalex.org/W6746044654","https://openalex.org/W6776559232","https://openalex.org/W6999307826","https://openalex.org/W7017903067","https://openalex.org/W7046093709"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"The":[0,110,133],"performance":[1],"of":[2,35,44,57,87,117,123,139,151,159,174,181],"machine":[3,64],"learning":[4,65],"models":[5,62],"depends":[6,31],"on":[7,32,148],"several":[8],"factors,":[9],"including":[10],"data":[11],"normalization,":[12],"which":[13],"can":[14],"significantly":[15],"improve":[16],"its":[17],"accuracy.":[18],"There":[19],"are":[20,78],"many":[21],"standardization":[22,166],"techniques,":[23],"and":[24,41,72,92,106,156,188],"none":[25],"is":[26,135],"universally":[27],"suitable;":[28],"the":[29,33,36,38,42,45,55,85,114,121,136,145,149,160,169,172,179],"choice":[30],"characteristics":[34],"problem,":[37],"predictive":[39],"task,":[40],"needs":[43],"model":[46],"used.":[47],"This":[48],"study":[49,170],"analyzes":[50],"how":[51,82],"normalization":[52,76,118],"techniques":[53,77],"influence":[54],"outcomes":[56],"real":[58],"estate":[59],"price":[60],"regression":[61,176],"using":[63],"to":[66,80,143,177],"uncover":[67],"complex":[68],"relationships":[69,88,162],"between":[70,89],"urban":[71],"economic":[73],"factors.":[74],"Six":[75],"employed":[79],"assess":[81],"they":[83],"affect":[84],"estimation":[86],"property":[90],"value":[91],"factors":[93],"like":[94],"social":[95],"degradation,":[96],"resident":[97],"population,":[98],"per":[99],"capita":[100],"income,":[101],"green":[102],"spaces,":[103],"building":[104],"conditions,":[105],"degraded":[107],"neighborhood":[108],"presence.":[109],"study\u2019s":[111],"findings":[112],"underscore":[113],"pivotal":[115],"role":[116],"in":[119],"shaping":[120],"perception":[122],"variables,":[124],"accentuating":[125],"critical":[126],"thresholds,":[127],"or":[128],"distorting":[129],"anticipated":[130],"functional":[131,161],"relationships.":[132],"work":[134],"first":[137],"application":[138],"a":[140],"methodological":[141],"approach":[142],"define":[144],"best":[146],"technique":[147],"basis":[150],"two":[152],"criteria:":[153],"statistical":[154],"reliability":[155],"empirical":[157],"evidence":[158],"obtainable":[163],"with":[164],"each":[165],"technique.":[167],"Notably,":[168],"underscores":[171],"potential":[173],"machine-learning-based":[175],"circumvent":[178],"limitations":[180],"conventional":[182],"models,":[183],"thereby":[184],"yielding":[185],"more":[186],"robust":[187],"interpretable":[189],"results.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
