The performance of one dimensional Naïve Bayes Classifier for Feature Selection in Predicting Prospective Car Insurance Buyers

Dilla Fadlillah Salma, Hendri Murfi, Devvi Sarwinda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

One of the products sold by insurance companies is car insurance. To offer this product, one of the techniques used by the company is cold calling. This method often decreases the sellers' mentalities because they face many rejections when offering insurance products. This problem can be reduced by classifying prospective buyers' data first. The data can be classified as customers with the potential to buy insurance and customers who have no potential to buy insurance. From the obtained data, there are certainly many features that support the classification process. However, not all features contributed to improving classification accuracy. Machine learning especially the method of feature selection helps to reduce dimensions and to improve classification accuracy. In this paper, we examine One-Dimensional Naïve Bayes Classifier (1-DBC) as a feature selection method that is applied to two classifier methods, i.e., Support Vector Machine and Logistic Regression. Our simulations show that the two classifiers can use fewer features to produce comparable accuracies in classifying prospective car insurance buyers.

Original languageEnglish
Title of host publicationData Mining and Big Data - 4th International Conference, DMBD 2019, Proceedings
EditorsYuhui Shi, Ying Tan
PublisherSpringer Verlag
Pages124-132
Number of pages9
ISBN (Print)9789813295629
DOIs
Publication statusPublished - 1 Jan 2019
Event4th International Conference on Data Mining and Big Data, DMBD 2019 - Chiang Mai, Thailand
Duration: 26 Jul 201930 Jul 2019

Publication series

NameCommunications in Computer and Information Science
Volume1071
ISSN (Print)1865-0929

Conference

Conference4th International Conference on Data Mining and Big Data, DMBD 2019
CountryThailand
CityChiang Mai
Period26/07/1930/07/19

Keywords

  • Car insurance
  • Feature selection
  • Logistic regression
  • One Dimensional Naïve Bayes Classifier
  • Support vector machine

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