Adaptive Gaussian Filtering
Free Version
Publisher Description
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++.
About Adaptive Gaussian Filtering
Adaptive Gaussian Filtering is a free software published in the Teaching & Training Tools list of programs, part of Education.
This Teaching & Training Tools program is available in English. It was last updated on 19 April, 2024. Adaptive Gaussian Filtering is compatible with the following operating systems: Linux, Mac, Windows.
The company that develops Adaptive Gaussian Filtering is peteysoft. The latest version released by its developer is 1.0. This version was rated by 1 users of our site and has an average rating of 4.0.
The download we have available for Adaptive Gaussian Filtering has a file size of 1.53 MB. Just click the green Download button above to start the downloading process. The program is listed on our website since 2014-12-06 and was downloaded 53 times. We have already checked if the download link is safe, however for your own protection we recommend that you scan the downloaded software with your antivirus. Your antivirus may detect the Adaptive Gaussian Filtering as malware if the download link is broken.
How to install Adaptive Gaussian Filtering on your Windows device:
- Click on the Download button on our website. This will start the download from the website of the developer.
- Once the Adaptive Gaussian Filtering is downloaded click on it to start the setup process (assuming you are on a desktop computer).
- When the installation is finished you should be able to see and run the program.
