Linear regression may not be suitable for count data as it can produce negative predictions, which don't make sense for certain types of data like the number of calls received. Poisson regression, a type of generalized linear model (GLM), is better suited for count-based responses as it assumes the data follows a Poisson distribution. It ensures non-negative predictions and acknowledges that outcomes are not equally likely around the mean.
Table of contents
Are you overwhelmed with the amount of information in ML/DS?Sort: