Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)

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Weight of Evidence and Information Value on Support Vector Machine Classifier

Authors
M Dika Saputra1, *, Zahroatul Fitria1, Bagus Sartono2, Evi Ramadhani3, Alfian Futuhul Hadi1
1Department of Postgraduate Mathematics, University of Jember, Jember, Indonesia
2Department of Statistics and Data Science , IPB University, Bogor, Indonesia
3Department of Statistics, Syiah Kuala University, Aceh, Indonesia
*Corresponding author. Email: m.dikasaputra963@gmail.com
Corresponding Author
M Dika Saputra
Available Online 22 May 2023.
DOI
10.2991/978-94-6463-174-6_11How to use a DOI?
Keywords
weight of evidence; information value; feature selection; classification; machine learning
Abstract

In building a classification model, variables containing low predictive information are sometimes used. This can increase the bias on classification. Weight of Evidence (WoE) and Information Value (IV) provide a good theoretical foundation to explore, filtering, and transforming variables in binary classification. The value of IV can help measure the predictive power possessed by a variable in separating binary classes. This research implements this framework to screen 24 predictor variables that will be used in the svm classification model to improve the evaluation of the food insecure household classification model. We use the National Socioeconomic Survey by the Indonesian Central Bureau of Statistics in 2020 for West Java Province and 2021 for East Java Province to produce a classification model. The results of this study showed that WOE was able to improve the model evaluation value from the AUC value of 0.81 to 0.83 for West Java Province and the AUC value of 0.58 to 0.66 for East Java Province.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
Series
Advances in Intelligent Systems Research
Publication Date
22 May 2023
ISBN
978-94-6463-174-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-174-6_11How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M Dika Saputra
AU  - Zahroatul Fitria
AU  - Bagus Sartono
AU  - Evi Ramadhani
AU  - Alfian Futuhul Hadi
PY  - 2023
DA  - 2023/05/22
TI  - Weight of Evidence and Information Value on Support Vector Machine Classifier
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 113
EP  - 124
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_11
DO  - 10.2991/978-94-6463-174-6_11
ID  - Saputra2023
ER  -