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Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms

Sapna Panigrahi1 , Bhakti Palkar2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 72-77, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.7277

Online published on Sep 30, 2018

Copyright © Sapna Panigrahi, Bhakti Palkar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Sapna Panigrahi, Bhakti Palkar, “Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.72-77, 2018.

MLA Style Citation: Sapna Panigrahi, Bhakti Palkar "Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms." International Journal of Computer Sciences and Engineering 6.9 (2018): 72-77.

APA Style Citation: Sapna Panigrahi, Bhakti Palkar, (2018). Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms. International Journal of Computer Sciences and Engineering, 6(9), 72-77.

BibTex Style Citation:
@article{Panigrahi_2018,
author = {Sapna Panigrahi, Bhakti Palkar},
title = {Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {72-77},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2824},
doi = {https://doi.org/10.26438/ijcse/v6i9.7277}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.7277}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2824
TI - Comparative Analysis on Classification Algorithms of Auto-Insurance Fraud Detection based on Feature Selection Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - Sapna Panigrahi, Bhakti Palkar
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 72-77
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

This paper is a comparative analysis of different machine learning algorithms used to detect fraud claims of Automobile/vehicle Insurance claims dataset. In this paper large dataset of automobile insurance claims is used and three feature selection algorithms are applied to the dataset which will be used by the classification algorithms to detect the fraud claims. The Feature Selection algorithms used in this paper are Tree-Based Feature Selection Algorithm, L1-Based Feature Selection Algorithm and Univariate Feature Selection Algorithm and the classification algorithms are Random Forest (RF), Naive Bayes(NB), K-Nearest Neighbor(KNN) and Decision Tree(DT). These algorithms are compared on the basis of performance measures such as accuracy, precision, recall. The proposed model shows that Random Forest works well with respect to accuracy and precision and Decision Tree is the best with respect to recall.

Key-Words / Index Term

Automobile Insurance,Machinelearning, Feature Selection Algorithms, Classification Algorithms

References

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