Gaussian kernel example

1. Why is Gaussian kernel better?
2. What is a Gaussian kernel?
3. What kernel to use for Gaussian process?
4. What is Gaussian kernel in machine learning?

Why is Gaussian kernel better?

Gaussian kernels are universal kernels i.e. their use with appropriate regularization guarantees a globally optimal predictor which minimizes both the estimation and approximation errors of a classifier.

What is a Gaussian kernel?

The Gaussian kernel is the physical equivalent of the mathematical point. It is not strictly local, like the mathematical point, but semi-local. It has a Gaussian weighted extent, indicated by its inner scale s.

What kernel to use for Gaussian process?

Perhaps the most widely used kernel is probably the radial basis function kernel (also called the quadratic exponential kernel, the squared exponential kernel or the Gaussian kernel): k(xₙ, xₘ) = exp(-||xₙ - xₘ||²/2L²), where L the kernel length scale.

What is Gaussian kernel in machine learning?

The Gaussian kernel is a very popular kernel function used in many machine learning algorithms, especially in support vector machines (SVMs). It is more often used than polynomial kernels when learning from nonlinear datasets and is usually employed in formulating the classical SVM for nonlinear problems.