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A library and a GUI front-end for fuzzy machine learning
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.
This is a soccer-themed, 3rd-person 3D sokoban puzzle game. It uses data in a format that is commonly found on the internet.
It has undo <u> and restart <r> functions. Comes with many puzzle files, each typically having dozens of "levels". The next <n> and previous <p> keys move between levels. The <Lshft> and <Rshft> keys move between the different puzzle files. The <z> key creates a setpoint (reZero) so that subsequent restarts restore that setpoint.
To move the "kicker" use the...
It is (no stack based!) VM in a form of a library. It supports different language paradigms without data type restrictions, allows both interpretation and JIT, produces a fast code. Our goal - to have a GENERIC and POWER tool for code migration.
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