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Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent...

Gnoga uses modern web technologies to allow simple creation of cross platform GUIs for Ada with native or custom look and feels that perform on par to native toolsets locally and can be easily and securely remoted as web apps over the internet as well.

Fuzzy sets for Ada is a library providing implementations of confidence factors with the operations not, and, or, xor, +, and *, classical fuzzy sets with the set-theoretic operations and the operations of the possibility theory, intuitionistic fuzzy sets with the operations on them, fuzzy logic based on the intuitionistic fuzzy sets and the possibility theory; fuzzy numbers, both integer and floating-point with conventional arithmetical operations, and linguistic variables and sets of...

The Simple components for Ada library provides implementations of smart pointers for automatically collected objects (using reference counting), object persistence, unbounded and bounded arrays of smart pointers, generic unbounded arrays of private objects and plain pointers, generic sets, maps, arbitrary precision arithmetic, B-trees, directed graphs, directed weighted graphs, stacks, and storage pools. It also includes table management, string editing, IEEE 754 support, and infix...