Nonparametric Regression
Explore nonparametric regression methods that allow fitting data locally rather than globally. Learn how nearest-neighbor and kernel regression techniques work, understand distance metrics, and discover how to achieve better predictions by weighing neighbors or data points. This lesson will help you deepen your grasp of advanced regression approaches useful in data science interviews and practical modeling.
We'll cover the following...
We worked on parametric approaches in the previous lesson. This lesson is dedicated to the nonparametric approach for regression.
Using the appropriate value of parameters, we can fit the data. But what if fitting the data is not possible with one model?
See the example below.
We can think of fitting a simple regression line on this data. It will look similar to this.
However, this is not ideal. Maybe we can try high order polynomials. See the example of fit below.
It is better than the previous solution, but it still does not capture the best model. What if we can fit the data locally (small points) instead of ...