The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan

© Springer International Publishing Switzerland 2014. We adapted the nonparametric evidence-theoretic k-Nearest Neighbor (k-NN) rule,whichwas originally designed formultinomial choice data, to rank-ordered choice data.The contribution of thismodel is its ability to extract information from all the o...

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Main Authors: Supanika Leurcharusmee, Peerapat Jatukannyaprateep, Songsak Sriboonchitta, Thierry Denoeux
Format: Book Series
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84921510354&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45670
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-456702018-01-24T06:14:51Z The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan Supanika Leurcharusmee Peerapat Jatukannyaprateep Songsak Sriboonchitta Thierry Denoeux © Springer International Publishing Switzerland 2014. We adapted the nonparametric evidence-theoretic k-Nearest Neighbor (k-NN) rule,whichwas originally designed formultinomial choice data, to rank-ordered choice data.The contribution of thismodel is its ability to extract information from all the observed rankings to improve the prediction power for each individual’s primary choice. The evidence-theoretic k-NNrule for heterogeneous rank-ordered datamethod can be consistently applied to complete and partial rank-ordered choice data. This model was used to predict an individual’s source of loan given his or her characteristics and also identify individual characteristics that help the prediction. The results show that the prediction from the rank-ordered choice model outperforms that of the traditionalmultinomial choicemodelwith only one observed choice. 2018-01-24T06:14:51Z 2018-01-24T06:14:51Z 2014-01-01 Book Series 16113349 03029743 2-s2.0-84921510354 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84921510354&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45670
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © Springer International Publishing Switzerland 2014. We adapted the nonparametric evidence-theoretic k-Nearest Neighbor (k-NN) rule,whichwas originally designed formultinomial choice data, to rank-ordered choice data.The contribution of thismodel is its ability to extract information from all the observed rankings to improve the prediction power for each individual’s primary choice. The evidence-theoretic k-NNrule for heterogeneous rank-ordered datamethod can be consistently applied to complete and partial rank-ordered choice data. This model was used to predict an individual’s source of loan given his or her characteristics and also identify individual characteristics that help the prediction. The results show that the prediction from the rank-ordered choice model outperforms that of the traditionalmultinomial choicemodelwith only one observed choice.
format Book Series
author Supanika Leurcharusmee
Peerapat Jatukannyaprateep
Songsak Sriboonchitta
Thierry Denoeux
spellingShingle Supanika Leurcharusmee
Peerapat Jatukannyaprateep
Songsak Sriboonchitta
Thierry Denoeux
The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
author_facet Supanika Leurcharusmee
Peerapat Jatukannyaprateep
Songsak Sriboonchitta
Thierry Denoeux
author_sort Supanika Leurcharusmee
title The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
title_short The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
title_full The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
title_fullStr The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
title_full_unstemmed The evidence-theoretic k-NN rule for rank-ordered data: Application to predict an individual’s source of loan
title_sort evidence-theoretic k-nn rule for rank-ordered data: application to predict an individual’s source of loan
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84921510354&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45670
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