Original language | English |
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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 |
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.