4 ms·
Once you find the N nearest neighbors, why consider only the 0th order (locally constant) model, which is what KNN assumes? Instead you can use a larger N and f
by Bostonian 5y ago
Once you find the N nearest neighbors, why consider only the 0th order (locally constant) model, which is what KNN assumes? Instead you can use a larger N and fit a local linear regression. I have tried this on synthetic data sets, and it works pretty well. This is common for 1D regression but not regression with multiple predictors.
- nestorD 5y agoOnce you do that you have something that starts looking like a Gaussian process but is a lot cheaper. I believe it could have a lot of value (for people who have too much data for Gaussian process but otherwise could do with their good properties and are in a space with an easily defined distance).