Today, if you ask any data scientist about the statistical methods, (or even a few) you will most likely discover that there are two most well-known statistical methods used within the practice of data science and the statistics industry today for predictive modeling. We introduced these two methods in Chapter 6, Database Progression to Database Regression.
These two methods are as follows:
- Linear regression
- Logistic regression
The linear regression method is probably considered to be the classic or most common starting point for problems, where the goal is to predict a numerical quantity. The Linear Regression (or LR) model is based on a linear combination of input features.
The logistic regression method uses a nonlinear transformation of this linear feature combination in order to restrict the range of the output in the interval [0, 1]. In doing...
