CHMMPP: A c++ library for constrained Hidden Markov Models
- Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
SAND2024-13027O The CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.
- Site Accession Number:
- SCR #3025.0
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Programming Language(s):
- C++
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOEPrimary Award/Contract Number:NA0003525
- DOE Contract Number:
- NA0003525
- Code ID:
- 145407
- OSTI ID:
- code-145407
- Country of Origin:
- United States
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