![]() ![]() ![]() The Negative Binomial (NB) regression model is one such model that does not make the variance = mean assumption about the data. In such cases, one needs to use a regression model that will not make the equi-dispersion assumptioni.e.not assume that variance=mean. Often, the variance is greater than the mean, a property called over-dispersion, and sometimes the variance is less than the mean, called under-dispersion. This rather strict criterion is often not satisfied by real world data. The low performance of the model was because the data did not obey the variance = mean criterion required of it by the Poisson regression model. Training summary for the Poisson regression model showing unacceptably high values for deviance and Pearson chi-squared statistics (Image by Author)
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