At first glance, machine learning seems to be distant from statistics. However, if we take a deeper look into them, we can draw parallels between both. In this chapter, we will deep dive into the details. Comparisons have been made between linear regression and lasso/ridge regression in order to provide a simple comparison between statistical modeling and machine learning. These are basic models in both worlds and are good to start with.
In this chapter, we will cover the following:
- Understanding of statistical parameters and diagnostics
- Compensating factors in machine learning models to equate statistical diagnostics
- Ridge and lasso regression
- Comparison of adjusted R-square with accuracy