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# 204.6.7 Soft Margin Classification – Noisy Data and Validation

##### What happens if the data is noisy with SVM?
Link to the previous post : https://statinfer.com/204-6-6-practice-kernel-non-linear-classifier/

## Soft Margin Classification – Noisy data

### Noisy data

• What if there is some noise in the data.
• What id the overall data can be classified perfectly except few points.
• How to find the hyperplane when few points are on the wrong side.

### Soft Margin Classification – Noisy data

• The non-separable cases can be solved by allowing a slack variable(x) for the point on the wrong side.
• We are allowing some errors while building the classifier.
• In SVM optimization problem we are initially adding some error and then finding the hyperplane.
• SVM will find the maximum margin classifier allowing some minimum error due to noise.
• Hard Margin -Classifying all data points correctly.
• Soft margin – Allowing some error.

### SVM Validation

• SVM doesn’t give us the probability, it directly gives us the resultant classes.
• Usual methods of validation like sensitivity, specificity, cross validation, ROC and AUC are the validation methods.

21st June 2017

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