Kernel Regression

#machine-learning #interview

We can use linear regression for non-linear data using high dimensional quadratic line
The problem is we don't know which polynomial to use
So we use Kernel Regression
Kernel Regression is a Non-parametric Method

Kernel Regression Formula

$f (x) = \frac{1}{N} \sum_{i = 1}^{N} w_{i} y_{i}$

where,

w_{i} = \frac{N k (\frac{x_{i} - x}{b})}{\sum_{l = 1}^{N} k (\frac{x_{l} - x}{b})}

$k ()$ most frequently used gaussian kernel

k (z) = \frac{1}{\sqrt{2 π}} \exp (\frac{- z^{2}}{2})

Related Notes