Local Averaging Predictors

This lecture introduces local averaging predictors, including K-nearest neighbors, histogram-based methods, and Nadaraya-Watson predictors. It covers the properties of local averaging predictors, the general framework of local empirical risk minimization, and local linear regression (LOWESS). The slides explain the principle of local averaging methods, different types of local averaging methods, convolution kernels, and Nadaraya-Watson estimators. It also discusses star velocity estimation with KNN, comments on local averaging methods, local empirical risk minimization, and local quadratic ERM. The lecture concludes with local linear regression, its applications, and generalizations to local polynomial and spline regression.