{"id":"https://openalex.org/W4407097745","doi":"https://doi.org/10.1109/access.2025.3537807","title":"Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania","display_name":"Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407097745","doi":"https://doi.org/10.1109/access.2025.3537807"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3537807","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3537807","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3537807","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050747528","display_name":"Ngong\u2019ho Bujiku Sende","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087849","display_name":"University of Rwanda","ror":"https://ror.org/00286hs46","country_code":"RW","type":"education","lineage":["https://openalex.org/I4210087849"]}],"countries":["RW"],"is_corresponding":false,"raw_author_name":"Ngong\u2019Ho Bujiku Sende","raw_affiliation_strings":["African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda"],"raw_orcid":"https://orcid.org/0009-0001-4185-3857","affiliations":[{"raw_affiliation_string":"African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda","institution_ids":["https://openalex.org/I4210087849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066292961","display_name":"Snehanshu Saha","orcid":"https://orcid.org/0000-0002-8458-604X"},"institutions":[{"id":"https://openalex.org/I4210148827","display_name":"Birla Institute of Technology and Science, Pilani - Goa Campus","ror":"https://ror.org/046sh6j17","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210148827","https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Snehanshu Saha","raw_affiliation_strings":["CSIS and APPCAIR, Birla Institute of Technology and Science Pilani Goa Campus, Zuarinagar, Goa, India","CSIS and APPCAIR, Birla Institute of Technology and Science Pilani Goa Campus, Goa, India"],"raw_orcid":"https://orcid.org/0000-0002-8458-604X","affiliations":[{"raw_affiliation_string":"CSIS and APPCAIR, Birla Institute of Technology and Science Pilani Goa Campus, Zuarinagar, Goa, India","institution_ids":["https://openalex.org/I4210148827"]},{"raw_affiliation_string":"CSIS and APPCAIR, Birla Institute of Technology and Science Pilani Goa Campus, Goa, India","institution_ids":["https://openalex.org/I4210148827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116132116","display_name":"Leon Ruganzu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087849","display_name":"University of Rwanda","ror":"https://ror.org/00286hs46","country_code":"RW","type":"education","lineage":["https://openalex.org/I4210087849"]}],"countries":["RW"],"is_corresponding":false,"raw_author_name":"Leon Ruganzu","raw_affiliation_strings":["African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda","African Centre of Excellence, Data Science University of Rwanda, Rwanda"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda","institution_ids":["https://openalex.org/I4210087849"]},{"raw_affiliation_string":"African Centre of Excellence, Data Science University of Rwanda, Rwanda","institution_ids":["https://openalex.org/I4210087849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078708105","display_name":"Saibal Kar","orcid":"https://orcid.org/0000-0001-8134-1517"},"institutions":[{"id":"https://openalex.org/I4210121529","display_name":"Centre for Studies in Social Sciences Calcutta","ror":"https://ror.org/024rfjv05","country_code":"IN","type":"facility","lineage":["https://openalex.org/I4210121529"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saibal Kar","raw_affiliation_strings":["Centre for Studies in Social Sciences, Calcutta, India, and IZA, Bonn, Germany","The Centre for Studies in Social Sciences at Calcutta, Kolkata, India"],"raw_orcid":"https://orcid.org/0000-0001-8134-1517","affiliations":[{"raw_affiliation_string":"Centre for Studies in Social Sciences, Calcutta, India, and IZA, Bonn, Germany","institution_ids":["https://openalex.org/I4210121529"]},{"raw_affiliation_string":"The Centre for Studies in Social Sciences at Calcutta, Kolkata, India","institution_ids":["https://openalex.org/I4210121529"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":21.3698,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.99177802,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"23461","last_page":"23471"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10446","display_name":"Income, Poverty, and Inequality","score":0.7649999856948853,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10446","display_name":"Income, Poverty, and Inequality","score":0.7649999856948853,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11886","display_name":"Agricultural risk and resilience","score":0.6908000111579895,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tanzania","display_name":"Tanzania","score":0.8696246147155762},{"id":"https://openalex.org/keywords/poverty","display_name":"Poverty","score":0.6402502059936523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6124898195266724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5281472206115723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4529872536659241},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4437965154647827},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25064098834991455},{"id":"https://openalex.org/keywords/socioeconomics","display_name":"Socioeconomics","score":0.2045503556728363},{"id":"https://openalex.org/keywords/economic-growth","display_name":"Economic growth","score":0.11540615558624268},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1099657416343689},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.08798372745513916}],"concepts":[{"id":"https://openalex.org/C2779357621","wikidata":"https://www.wikidata.org/wiki/Q655495","display_name":"Tanzania","level":2,"score":0.8696246147155762},{"id":"https://openalex.org/C189326681","wikidata":"https://www.wikidata.org/wiki/Q10294","display_name":"Poverty","level":2,"score":0.6402502059936523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6124898195266724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5281472206115723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4529872536659241},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4437965154647827},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25064098834991455},{"id":"https://openalex.org/C45355965","wikidata":"https://www.wikidata.org/wiki/Q1643441","display_name":"Socioeconomics","level":1,"score":0.2045503556728363},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.11540615558624268},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1099657416343689},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.08798372745513916}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3537807","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3537807","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:41ffffd431054b7fa404f922f4725edd","is_oa":true,"landing_page_url":"https://doaj.org/article/41ffffd431054b7fa404f922f4725edd","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":"IEEE Access, Vol 13, Pp 23461-23471 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3537807","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3537807","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1967903496","https://openalex.org/W2144412017","https://openalex.org/W2168396533","https://openalex.org/W2301889354","https://openalex.org/W2465642162","https://openalex.org/W2513506629","https://openalex.org/W2782709293","https://openalex.org/W2897516981","https://openalex.org/W2911810052","https://openalex.org/W2914768946","https://openalex.org/W2946189999","https://openalex.org/W2997208123","https://openalex.org/W2999806019","https://openalex.org/W3021556882","https://openalex.org/W3029476589","https://openalex.org/W3035176269","https://openalex.org/W3128861468","https://openalex.org/W3158548809","https://openalex.org/W3190329128","https://openalex.org/W4200003491","https://openalex.org/W4210815411","https://openalex.org/W4220694460","https://openalex.org/W4229367534","https://openalex.org/W4233787546","https://openalex.org/W4285450698","https://openalex.org/W4295007742","https://openalex.org/W4298122515","https://openalex.org/W4307703018","https://openalex.org/W4307951689","https://openalex.org/W4318822325","https://openalex.org/W4327753856","https://openalex.org/W4376139057","https://openalex.org/W4385556979","https://openalex.org/W4387066065","https://openalex.org/W4392714571","https://openalex.org/W6633953710","https://openalex.org/W6787018327","https://openalex.org/W6804129184","https://openalex.org/W6847648466","https://openalex.org/W6851194726","https://openalex.org/W6871781166"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Over":[0],"fifty":[1],"percent":[2],"of":[3,13,35,42,54,77,84,174,219],"the":[4,14,24,52,66,73,136,144,167,175,191,197,203,217,220],"population":[5],"in":[6,92,96,100],"Tanzania":[7,74],"suffers":[8],"from":[9,65,72,139],"multidimensional":[10,48,128],"poverty.":[11],"Because":[12],"high":[15],"poverty":[16,22,49,129],"rate":[17],"and":[18,29,33,68,120,153,161,172,209],"slow":[19],"improvement,":[20],"ending":[21],"by":[23],"year":[25],"2030":[26],"remains":[27],"challenging":[28],"empirically":[30],"testable":[31],"proposition":[32],"part":[34],"a":[36],"shared":[37],"challenge.":[38],"The":[39,147],"main":[40],"purpose":[41],"this":[43,61],"study":[44,148],"is":[45],"to":[46,126,141,165,170,190],"predict":[47,127],"status":[50,130],"with":[51],"help":[53],"best":[55,204],"performance-supervised":[56],"machine-learning":[57,86],"algorithms.":[58,176],"To":[59],"achieve":[60],"objective,":[62],"longitudinal":[63],"data":[64,150,179],"2014/15":[67],"2020/21":[69],"surveys,":[70],"sourced":[71],"National":[75],"Bureau":[76],"Statistics":[78],"(NBS)":[79],"were":[80,124],"analyzed.":[81],"A":[82],"variety":[83],"supervised":[85],"algorithms":[87],"such":[88],"as":[89],"RBF":[90],"Kernel":[91,95,99],"SVM,":[93,97,101],"Linear":[94],"Polynomial":[98],"Random":[102],"Forest,":[103],"Logistic":[104],"regression":[105],"classifier,":[106],"Decision":[107],"tree,":[108],"Gradient":[109],"Boosting,":[110],"K-Nearest":[111],"Neighbours":[112],"Classifier,":[113,116],"Na\u00efve":[114],"Bayes":[115],"Artificial":[117],"Neuron":[118],"Network":[119],"Ensemble":[121,198],"Learning":[122,199],"Model":[123,200],"implemented":[125],"for":[131],"each":[132],"dataset.":[133],"This":[134],"captured":[135],"dynamic":[137],"changes":[138],"2014":[140],"2021":[142],"at":[143],"national":[145],"level.":[146],"employed":[149],"pre-processing":[151],"techniques":[152],"adjusted":[154],"imbalance":[155],"through":[156],"weighted":[157],"categorical":[158],"cross":[159],"entropy":[160],"5-Fold":[162],"Cross":[163],"Validation":[164],"mitigate":[166],"inefficiencies":[168],"due":[169],"overfitting":[171],"under-fitting":[173],"Additionally,":[177],"dimensionality":[178],"reduction":[180],"was":[181],"performed":[182],"using":[183],"Principal":[184],"Component":[185],"Analysis":[186],"(PCA).":[187],"With":[188],"regard":[189],"evaluation":[192],"metrics,":[193],"we":[194],"show":[195],"that":[196],"has":[201],"achieved":[202],"performance":[205],"modelling":[206],"both":[207],"balanced":[208],"unbalanced":[210],"datasets.":[211],"Our":[212],"policy":[213],"recommendations":[214],"draw":[215],"on":[216],"results":[218],"algorithmic":[221],"predictions.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2025-10-10T00:00:00"}
