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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. ...
Some small command line programs and a file parser for Concept Explorer (conexp) written in C++. Currently features include: Converters from concept explorer into PDF, PostScript, SVG and PovRay, a modified 3D Freese layout.