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Created 4 years ago
SUPPORT VECTOR REGRESSION ( SVM )
INTRODUCTION & INTUTION
- SVR performs linear regression in higher dimensions
- In simple regression we try to minimise the error rate. While in SVR we try to fit the error within a certain threshold
- In Linear regession we try to minimize the error between the predicted and data. In SVR our goal is to make sure that errors do not exceed the threshold
- Advantage of SVR over OLSE linear regression is SVR can minimize overfitting problem.