On the importance of outlier detection

One of the biggest challenges in handling data is the presence of measurements that makes it difficult to construct a model that possesses a satisfying goodness of fit or, more importantly, a reliable goodness of prediction. This can range from measurements in production data to individuals responding to surveys. A question that immediately poses itself is “what is... Continue Reading →

Generating Sierpinski triangles with R

The other day I saw a cool video on how to generate a Sierpinski triangle. For you who have never heard of such a thing it is like a fractal tri-force from the Zelda games (wiki). The main idea for how to numerically generate the Sierpinski follows this simple algorithm: 1. Pick a random point,... Continue Reading →

Artificial Neural Networks and Patient Segmentation

Introduction Segmentation has for the past decades been a must for many businesses around the world. In a growingly competitive market in which understanding costumers (and keeping them) can be the difference between a flourishing business and a stagnating one, the need for efficient and accurate methods of segmentation is primordial. Some businesses have underestimated... Continue Reading →

Powered by WordPress.com.

Up ↑