A powerful MATLAB toolbox for basic static and dynamic probabilistic models. #MATLAB toolbox #Probabilistic model #Gaussian mixture #MATLAB #Toolbox #Toolkit
The HP Probabilistic Model Toolbox (PMT) for MATLAB contains a set of MATLAB & C functions one can use to build basic static & dynamic probabilistic models. Current PMT provides support for the following probabilistic models: · Gaussian mixtures, · Factor analyzers, · Markov chains, · Hidden Markov models, and · Linear dynamic systems.
For each probabilistic model, PMT provides functions for: · Simulation (sampling from the model) · Inference (hidden state estimation) · Learning model parameters from data
PMT supports multiple inference methods, both exact and approximate (e.g., winner takes all.) Model parameters are learned from data using maximum likelihood estimation (MLE). PMT also supports arbitrary distributions of training data.
Give Probabilistic Model Toolkit a try to see what it's all about!
- runs on:
- Windows All
- file size:
- 132 KB
- filename:
- pmt.zip
- main category:
- Programming
- developer:
- visit homepage
IrfanView
4k Video Downloader
Zoom Client
Bitdefender Antivirus Free
ShareX
calibre
Microsoft Teams
7-Zip
Windows Sandbox Launcher
Context Menu Manager
- 7-Zip
- Windows Sandbox Launcher
- Context Menu Manager
- IrfanView
- 4k Video Downloader
- Zoom Client
- Bitdefender Antivirus Free
- ShareX
- calibre
- Microsoft Teams