### What is the C Parameter?

* The C parameter tells the SVM optimization how much you want to avoid misclassifying each training example.
* For large values of C, the optimization will choose a smaller-margin hyperplane if that hyperplane does a better job of getting all the training points classified correctly.
* Conversely, a very small value of C will cause the optimizer to look for a larger-margin separating hyperplane, even if that hyperplane misclassifies more points.
* For very tiny values of C, you should get misclassified examples, often even if your training data is linearly separable.