Using a Customized Cost Function to deal with Unbalanced Data

As pointed in this Kdnuggets article, it's often the case that we only have a few examples of the thing that we want to predict in our data. The use cases are countless: only a small part of our website visitors purchase eventually, only a few of our transactions are fraudulent, etc. This is a real problem when using Machine Learning. That's because the algorithms usually need many examples of each class to extract the general rules in your data, and the instances in minority classes can be discarded as noise, causing some useful rules to never be found. The Kdnuggets article explained several techniques that can be used to address this problem.