| 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 | 603-606pp |
| Volume | 6 |
| ISBN (Print) | 9780387307688 |
| DOIs | |
| Publication status | Published - 2010 |
Abstract
Linear Regression is an instance of the Regression problem which is an approach to modelling a functional relationship between input variables x and an output/response variable y. In linear regression, a linear function of the input variables is used, and more generally a linear function of some vector function of the input variables Ï•(x) can also be used. The linear function estimates the mean of y (or more generally the median or a quantile).
Fingerprint
Dive into the research topics of 'Linear Regression'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver