In this article, we consider sufficient dimension folding for the regression mean function when predictors are matrix- or array-valued. We propose a new concept named central mean dimension folding ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the price of a particular make and model of a used car based on its ...

A two-step nonparametric regression quantile smoothing technique is presented here, combining a standard k-NN technique and a locally linear kernel smoother. There ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

Linear regression may be the most basic and accessible machine learning (ML) algorithm, but it’s also one of the fastest and most powerful. As a result, professionals in business, science, and ...