SQL Server 2017 Developer's Guide

Predicting with logistic regression

A logistic regression model consists of input units and an output unit, which is the predicted value. Input units are combined into a single transformed output value. This calculation uses the unit's activation function. An activation function has two parts: the first part is the combination function and merges all of the inputs into a single value (weighted sum, for example); the second part is the transfer function, which transfers the value of the combination function to the output value of the unit. The transfer function is called the sigmoid or logistic function and is S-shaped. Training a logistic regression model is the process of setting the best weights on the inputs of each of the units to maximize ...