By Sergey Yengoyan, Software Engineer
As the number of mobile apps continues to grow at a rapid pace, any dimensionality reduction method that helps decrease the size of a prediction model can improve performance.
For an interest profile consisting of three apps, we would have six training samples, as shown in the figure below:
So the model represented by the weights is a predictor of what other apps the user might already have. We not only achieve effective vectorization of the app appearances, but also have a tool to predict user interest.
As the saying goes: “If you are targeting everyone, you are not targeting anyone.” At Aarki, our data scientists are constantly experimenting to develop sophisticated machine learning algorithms that allow us a better understanding of our data and better predict user profiles. That’s how we reach and acquire the best users and deliver strong ROI to our clients.