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What is Generalized Linear Model

Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
A modeling process that build relationships between variables. It relaxes the restrictive normal assumptions for the traditional linear regression model, which allows GLM capable of analyzing non-normal data.
Published in Chapter:
Automobile Fatal Accident and Insurance Claim Analysis Through Artificial Neural Network
Xiangming Liu (University of Connecticut, USA) and Gao Niu (Bryant University, USA)
DOI: 10.4018/978-1-7998-8455-2.ch009
Abstract
This chapter presents a thorough descriptive analysis of automobile fatal accident and insurance claims data. Major components of the artificial neural network (ANN) are discussed, and parameters are investigated and carefully selected to ensure an efficient model construction. A prediction model is constructed through ANN as well as generalized linear model (GLM) for model comparison purposes. The authors conclude that ANN performs better than GLM in predicting data for automobile fatalities data but does not outperform for the insurance claims data because automobile fatalities data has a more complex data structure than the insurance claims data.
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Visualization Tools for Big Data Analytics in Quantitative Chemical Analysis: A Tutorial in Chemometrics
Is a flexible generalization of ordinary Linear Regression that allows for response variables that have error distribution models other than a normal distribution.
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