Open Source Ada Information Analysis Software

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 features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.

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 linguistic variables with operations on them. String-oriented I/O is supported. A rich set of GTK+ GUI widgets is provided.