# 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.

## 3,947 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.

### Support vector regression with random output variable and probabilistic constraints

- Computer Science
- 2017

A new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions, and the optimal hyperplane regression can be obtained by solving a quadratic optimization problem.

### 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.

### Fast Processing in Support Vector Machine for Large-Scaled Data Set

- Computer Science
- 2012

A new reduction strategy is proposed for training support vector machines with large-scale data set based on the analysis of the nature and difficulties in training SVM.

### 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.

### 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…

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