This software is a Java-based implementation of Hidden Markov Models (HMM) that can be used for training and prediction purposes. HMM is a powerful machine learning technique that can be applied to problems that involve predicting future events based on past observations.
The jHMM software is a free and open source Java library that is designed to handle Hidden Markov Models. With the ability to encode models in a simple XML format, users can create arbitrary states, transitions, and alphabets to fully customize their models.
The jHMM library is equipped with sequence state predictions and Baum-Welch training, allowing users to fine-tune their model parameters for optimized results. This feature allows users to achieve greater accuracy in their predictions and outcomes.
It is important to note that jHMM is distributed and licensed under the terms of the BSD License, providing users with the confidence and security they need when utilizing this powerful software. Overall, jHMM is a valuable tool for anyone looking to create and manipulate Hidden Markov Models with ease and accuracy.
The jHMM library is equipped with sequence state predictions and Baum-Welch training, allowing users to fine-tune their model parameters for optimized results. This feature allows users to achieve greater accuracy in their predictions and outcomes.
It is important to note that jHMM is distributed and licensed under the terms of the BSD License, providing users with the confidence and security they need when utilizing this powerful software. Overall, jHMM is a valuable tool for anyone looking to create and manipulate Hidden Markov Models with ease and accuracy.
What's New
Version 1.1.0: N/A