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Support vector machine for spatial variation / C. Andris in Transactions in GIS, vol 17 n° 1 (February 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 1 (February 2013) . - pp 40 - 61 Titre : Support vector machine for spatial variation Type de document : Article/Communication Auteurs : C. Andris, Auteur ; D. Cowen, Auteur ; J. Wittenbach, Auteur Année de publication : 2013 Article en page(s) : pp 40 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse discriminante [Termes IGN] classification barycentrique [Termes IGN] classification dirigée [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] exploration de données géographiques [Termes IGN] seuillage Résumé : (Auteur) Large, multivariate geographic datasets have been used to characterize geographic space with the help of spatial data mining tools. In our study, we explore the sufficiency of the Support Vector Machine (SVM), a popular machine-learning technique for unsupervised classification and clustering, to help recognize hidden patterns in a college admissions dataset. Our college admissions dataset holds over 10,000 students applying to an undisclosed university during one undisclosed year. Students are qualified almost exclusively by their standardized test scores and school records, and a known admissions decision is rendered based on these criteria. Given that the university has a number of political, social and geographic econometric factors in its admissions decisions, we use SVM to find implicit spatial patterns that may favor students from certain geographic regions. We first explore the characteristics of the applicants in the college admissions case study. Next, we explain the SVM technique and our unique ‘threshold line’ methodology for both discrete (regional) and continuous (k-neighbors) space. We then analyze the results of the regional and k-neighbor tests in order to respond to the methodological and geographic research questions. Numéro de notice : A2013-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01354.x Date de publication en ligne : 09/10/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01354.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32177 [article]