In this section, we will look at two important modeling techniques, known as linear optimization and the linear regressionmodel. In the previous chapter, we learned about deep learning, neural networks, decision trees, and reinforcement learning.
Linear optimization
Used frequently in supply chain businesses, the linear optimization model seeks to achieve the optimization objective (that is, to maximize profit or minimize cost) by changing some variables while considering some constraints. In the case of linear optimization, we also implement the structure similar to that of the capital structure optimization process.
This is not a machine learning model as we do not need to train the machine to learn any patterns.
The linear regression model
This is typically known as the regression model. What it does is find out the causation of some factors of the outcome. The outcome has to be numeric values. In statistics, some...
