Month: May 2016

This is the last post in series about Support Vector Machine classifier. We already feel the basics of SVM. We have our data preprocessed. Finally, we know the influence of some major hyperparameters on the classifier. Now, let's choose proper hyperparameters for a given problem. This is done by validation or cross-validation. These techniques are very common in Machine Learning and are also helpful in finding a proper SVM model. The example will cover building the classifier for the foreground/background estimation problem in Flover project.
More SVM model selection - how to adjust all these knobs pt. 2

Flover Project