Hidden Markov Models

Aegis designs and implements Hidden Markov Models for advanced data analytics. The Hidden Markov Model (HMM) is a powerful applied probability tool that excels at modeling dynamic processes and analyzing data generated by dynamic processes. The HMM is applied in some of the most successful pattern recognition algorithms in the world. Application of HMMs includes:

• Forensic information technology applications for tracking the identity of internet users;
• Classifying customers into marketing categories based on historical purchasing patterns;
• Identifying behavior predictive of machine failure or customer attrition.