Why Machine Learning
This lesson will focus on why we need machine learning models for predictions.
We'll cover the following...
Issues with Regression
In the previous chapter, we learned how to use linear and logistic regression models for making predictions from data. But there are some issues with the regression framework. We will look at these issues one by one.
Non-linear relationships
By design, linear regression explores linear relationships between the dependent and independent variables. It assumes that there is a straight-line relationship between the variables and tries to find the line that best fits the data. Sometimes, it is not the case that variables follow a linear relationship. For instance, the relationship between age and income is not linear. Income rises exponentially during the early years and then grows almost linearly at the later stages.
Linear Regression parameters converge on the mean of the predicted variable
Linear ...