Fuzzy machine learning framework

swMATH ID: 5893
Software Authors: kazakov
Description: 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; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.
Homepage: http://freecode.com/urls/e8fd13dc25b4142bafb5ba8814993444
Programming Languages: Ada 2005, GNADE ODBC, GTK+, GtkAda, SQLite
Keywords: fuzzy; machine learning; decision tree; fuzzy logic; Scientific/Engineering; Artificial Intelligence; Mathematics
Cited in: 0 Publications