Machine learning in non-stationary environments : introduction to covariate shift adaptation /
This volume focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) changes but the conditional distributions of outputs (answers) is unchanged, and presents machine learning theory algorithms, and applications to overcome this variet...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cambridge, Mass. :
MIT Press,
©2012.
|
| Series: | Adaptive computation and machine learning
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | This volume focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) changes but the conditional distributions of outputs (answers) is unchanged, and presents machine learning theory algorithms, and applications to overcome this variety of non-stationarity. |
|---|---|
| Physical Description: | 1 online resource (xiv, 261 pages) : illustrations. |
| ISBN: | 9780262301220 0262301229 1280499222 9781280499227 |
| DOI: | 10.7551/mitpress/9780262017091.001.0001 |