Distribution of claims in one year.

<div><p>Accurate forecasting of claim frequency in automobile insurance is essential for insurers to assess risks effectively and establish appropriate pricing policies. Traditional methods typically rely on a Poisson distribution for modeling claim counts; however, this approach can be...

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Bibliographic Details
Main Author:	Gadir Alomair (20490463) (author)
Published:	2024
Subjects:	Medicine Biotechnology Sociology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified assess risks effectively artificial neural network modeling claim counts comparative analysis using data characteristic common enhancing prediction accuracy claim frequency predictions study offers insights inflated negative binomial automobile claim data improving forecast accuracy zero inflation occurs claim frequency negative binomial claim periods inflated poisson comparative evaluation automobile insurance predictive accuracy zero inflation traditional poisson svm ), study investigates standard poisson single dataset results reveal research involved random forest predictive analytics poisson distribution machine learning insurance dataset including poisson inadequate due handling zero frequent zero
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Distribution of claims in one year.

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