{"id":"https://openalex.org/W111167776","doi":"https://doi.org/10.1007/978-3-642-29063-3_14","title":"Comparing Support Vector Regression and Statistical Linear Regression for Predicting Poverty Incidence in Vietnam","display_name":"Comparing Support Vector Regression and Statistical Linear Regression for Predicting Poverty Incidence in Vietnam","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W111167776","doi":"https://doi.org/10.1007/978-3-642-29063-3_14","mag":"111167776"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-29063-3_14","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-29063-3_14","pdf_url":null,"source":{"id":"https://openalex.org/S4210190054","display_name":"Lecture notes in geoinformation and cartography","issn_l":"1863-2246","issn":["1863-2246","1863-2351"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Geoinformation and Cartography","raw_type":"book-chapter"},"type":"book-chapter","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/A5067730563","display_name":"Cornelius Senf","orcid":"https://orcid.org/0000-0002-2389-2158"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Cornelius Senf","raw_affiliation_strings":["Geography Department, Geomatics Lab, Humboldt-University of Berlin, Unter den Linden 6, 10099, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Geography Department, Geomatics Lab, Humboldt-University of Berlin, Unter den Linden 6, 10099, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078698089","display_name":"Tobia Lakes","orcid":"https://orcid.org/0000-0001-8443-7899"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobia Lakes","raw_affiliation_strings":["Geography Department, Geomatics Lab, Humboldt-University of Berlin, Unter den Linden 6, 10099, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Geography Department, Geomatics Lab, Humboldt-University of Berlin, Unter den Linden 6, 10099, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067730563"],"corresponding_institution_ids":["https://openalex.org/I39343248"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.02429304,"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":"251","last_page":"265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10446","display_name":"Income, Poverty, and Inequality","score":0.996399998664856,"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":0.996399998664856,"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.972100019454956,"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/T11886","display_name":"Agricultural risk and resilience","score":0.9674000144004822,"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/statistics","display_name":"Statistics","score":0.5965350866317749},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5268615484237671},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5212641358375549},{"id":"https://openalex.org/keywords/incidence","display_name":"Incidence (geometry)","score":0.44133979082107544},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.431606650352478},{"id":"https://openalex.org/keywords/cross-sectional-regression","display_name":"Cross-sectional regression","score":0.43081605434417725},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.42817923426628113},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4222058951854706},{"id":"https://openalex.org/keywords/bayesian-multivariate-linear-regression","display_name":"Bayesian multivariate linear regression","score":0.39853835105895996},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.370572566986084},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.32216477394104004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22247254848480225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15113788843154907}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5965350866317749},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5268615484237671},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5212641358375549},{"id":"https://openalex.org/C61511704","wikidata":"https://www.wikidata.org/wiki/Q1671857","display_name":"Incidence (geometry)","level":2,"score":0.44133979082107544},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.431606650352478},{"id":"https://openalex.org/C90157343","wikidata":"https://www.wikidata.org/wiki/Q5188196","display_name":"Cross-sectional regression","level":4,"score":0.43081605434417725},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.42817923426628113},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4222058951854706},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.39853835105895996},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.370572566986084},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.32216477394104004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22247254848480225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15113788843154907},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-642-29063-3_14","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-29063-3_14","pdf_url":null,"source":{"id":"https://openalex.org/S4210190054","display_name":"Lecture notes in geoinformation and cartography","issn_l":"1863-2246","issn":["1863-2246","1863-2351"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Geoinformation and Cartography","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W349248956","https://openalex.org/W426092880","https://openalex.org/W1521365974","https://openalex.org/W1535928665","https://openalex.org/W1991128722","https://openalex.org/W2008974154","https://openalex.org/W2020009149","https://openalex.org/W2027336552","https://openalex.org/W2073981548","https://openalex.org/W2095600587","https://openalex.org/W2101804234","https://openalex.org/W2104445609","https://openalex.org/W2109943925","https://openalex.org/W2118898434","https://openalex.org/W2136781399","https://openalex.org/W2147330627","https://openalex.org/W2151376769","https://openalex.org/W2153635508","https://openalex.org/W2158031389","https://openalex.org/W2189257379","https://openalex.org/W2288770555","https://openalex.org/W2366205637","https://openalex.org/W2928802325","https://openalex.org/W3140868290","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2606692828","https://openalex.org/W4309298396","https://openalex.org/W2074089485","https://openalex.org/W2378624038","https://openalex.org/W2140265721","https://openalex.org/W31220157","https://openalex.org/W3199622279","https://openalex.org/W3035695858","https://openalex.org/W2349373437","https://openalex.org/W2349542682"],"abstract_inverted_index":null,"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-01-15T23:16:33.117629","created_date":"2025-10-10T00:00:00"}
