Regression

Novi Quadrianto; Wray Buntine

Regression

Novi Quadrianto
, Wray Buntine

Research output: Chapter in Book/Report/Conference proceeding › Entry for encyclopedia/dictionary › peer-review

Abstract

Regression is a fundamental problem in statistics and machine learning. In regression studies, we are typically interested in inferring a real-valued function (called a regression function) whose values correspond to the mean of a dependent (or response or output) variable conditioned on one or more independent (or input) variables. Many different techniques for estimating this regression function have been developed, including parametric, semi-parametric, and nonparametric methods.

Original language	English
Title of host publication	Encyclopedia of Machine Learning
Editors	Claude Sammut & Geoffrey I.Webb
Place of Publication	New York
Publisher	Springer
Pages	5pp
Volume	6
ISBN (Print)	9780387307688
Publication status	Published - 2010

Cite this

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title = "Regression",

abstract = "Regression is a fundamental problem in statistics and machine learning. In regression studies, we are typically interested in inferring a real-valued function (called a regression function) whose values correspond to the mean of a dependent (or response or output) variable conditioned on one or more independent (or input) variables. Many different techniques for estimating this regression function have been developed, including parametric, semi-parametric, and nonparametric methods.",

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AB - Regression is a fundamental problem in statistics and machine learning. In regression studies, we are typically interested in inferring a real-valued function (called a regression function) whose values correspond to the mean of a dependent (or response or output) variable conditioned on one or more independent (or input) variables. Many different techniques for estimating this regression function have been developed, including parametric, semi-parametric, and nonparametric methods.

M3 - Entry for encyclopedia/dictionary

SN - 9780387307688

VL - 6

SP - 5pp

BT - Encyclopedia of Machine Learning

A2 - null, Claude Sammut & Geoffrey I.Webb

PB - Springer

CY - New York

ER -

Regression

Abstract

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