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++.

Project Samples

Project Activity

See All Activity >

License

GNU General Public License version 2.0 (GPLv2)

Follow Adaptive Gaussian Filtering

Adaptive Gaussian Filtering Web Site

Other Useful Business Software
Unitrends | Unified Backup and Disaster Recovery You Can Rely On Icon
Unitrends | Unified Backup and Disaster Recovery You Can Rely On

A single user interface allows you to easily manage backups for cloud, SaaS, data centers and endpoints.

We’re here to help you conquer the complexity of backup and recovery. Our intelligent solutions are built to defend data against ransomware, data loss and downtime – no matter where the data lives.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Adaptive Gaussian Filtering!

Additional Project Details

Intended Audience

Non-Profit Organizations, Information Technology, Science/Research, Advanced End Users, Developers

User Interface

Command-line, Other toolkit

Programming Language

C++

Database Environment

Flat-file, Proprietary file format

Related Categories

C++ Information Analysis Software, C++ Machine Learning Software, C++ Statistics Software

Registered

2007-10-18