Preface

During my graduate school years I became acquainted with the field of machine learning, and in particular the field of pattern recognition. The focus of my work was on mathematical modeling and numerical simulations, but the ability to recognize patterns in a large volume of data had obvious applications in many fields. The years that followed brought me closer to the subject of machine learning than I ever imagined.

In 1999 I left academia and started working in industry. In one of my consulting projects, we were trying to identify the risk of heart failure for patients based (primarily) on their EKGs. In problems of that nature, an exact mathematical formulation is either unavailable or impractical to implement. Modeling work (our software) had to rely on methods that could adopt their predictive capability based on a given number of patient records, whose risk of heart failure was already diagnosed by a cardiologist. In other words, we were looking for methods that could “learn” from their input.