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It is one of the most widely known modeling technique. Linear regression is usually among the first few topics which people pick while learning predictive modeling. In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regression line is linear.
A Poisson regression model is sometimes known as a log-linear model, especially when used to model contingency tables. Poisson regression models are generalized linear models with the logarithm as the (canonical) link function, and the Poisson distribution function.n these examples, exposure is respectively unit area, personâyears and unit time. In Poisson regression this is handled as an offset, where the exposure variable enters on the right-hand side of the equation, but with a parameter estimate (for log(exposure)) constrained to 1. which implies.