I was going through the below-mentioned article:

And here goes the question

- Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?

And the answer in the article is: The model would consider only the points close to the hyperplane for modeling.

Actually, gamma or sigma in RBF is a nice approximation to K in KNN. so if the sigma value is high, then the model would consider even far away points.

You can try plotting using plot(exp(-x^2/(2*sigma^2))) in google.

Any explanations?