# Support Vector Regression Machines

@inproceedings{Drucker1996SupportVR, title={Support Vector Regression Machines}, author={Harris Drucker and Christopher J. C. Burges and Linda Kaufman and Alex Smola and Vladimir Naumovich Vapnik}, booktitle={NIPS}, year={1996} }

A new regression technique based on Vapnik's concept of support vectors is introduced. We compare support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space. On the basis of these experiments, it is expected that SVR will have advantages in high dimensionality space because SVR optimization does not depend on the dimensionality of the input space.

## 4,038 Citations

### Stochastic support vector regression with probabilistic constraints

- Computer Science, MathematicsApplied Intelligence
- 2017

A novel model of SVR is introduced in which any training samples containing inputs and outputs are considered the random variables with known or unknown distribution functions which helps to obtain maximum margin and achieve robustness.

### Interval Regression Analysis with Reduced Support Vector Machine

- Computer Science
- 2007

This paper introduces the principle of RSVM to evaluate interval regression analysis and shows that it has been proved more efficient than the traditional SVM in processing large-scaled data.

### Balanced Support Vector Regression

- Computer Science, MathematicsICAISC
- 2015

A method to incorporate the idea of regression to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem with improved generalization performance for suboptimal values of e and δ.

### Support vector machines: hype or hallelujah?

- Computer ScienceSKDD
- 2000

An intuitive explanation of SVMs from a geometric perspective is provided and the classification problem is used to investigate the basic concepts behind SVMs and to examine their strengths and weaknesses from a data mining perspective.

### Support Vector Regression

- Computer Science
- 2007

An attempt has been made to review the existing theory, methods, recent developments and scopes of Support Vector Regression.

### Bootstrap Based Pattern Selection for Support Vector Regression

- Computer SciencePAKDD
- 2008

A pattern selection method designed specifically for Support Vector Regression (SVR), where only a few patterns called support vectors are used to construct the regression model while other patterns are not used at all.

### Kernel Support Vector Regression with imprecise output

- Computer Science
- 2008

We consider a regression problem where uncertainty aects to the dependent variable of the elements of the database. A model based on the standard -Support Vector Regression approach is given, where…

### Feature selection for support vector regression via Kernel penalization

- Computer ScienceThe 2010 International Joint Conference on Neural Networks (IJCNN)
- 2010

This paper presents a novel feature selection approach (KP-SVR) that determines a non-linear regression function with minimal error and simultaneously minimizes the number of features by penalizing…

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