Azure ML comes with a bunch of popular regression algorithms. This section briefly describes other algorithms available (at the time of writing of this book) that we have not discussed so far:
The Bayesian Linear Regression Model: This model uses Bayesian Inference for regression. This may not be difficult to train as long as you get the regularization parameter right, which may fit a value such as 0.1, 0.2, and so on.
The Ordinal Regression Model: You use this when you have to train a model for a dataset in which the labels or target values have a natural ordering or ranking among them.
The Poisson Regression: It is a special type of regression analysis. It is typically used for model counts, for example, modeling the number of cold and flu cases associated with airplane flights or estimating the number of calls related to an event or promotion and so on.