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What is currently available
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Fuzzy graph-schemes in pattern recognition. The work covers the issue of building fuzzy learning systems using decision trees. The classical approach of learning with a teacher is extended to the case when the learning set contains fuzzy data.
Similarly the decision trees are generalized for the fuzzy case. The possibilities theory is consequently used. All data are specified in terms of
possibility and necessity (in Russian!) |
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Fuzzy machine
learning framework. 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; advanced graphical user interface based on GTK+; examples of
use. |
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On intuitionistic fuzzy machine
learning. The aim of this work is to propose an
intuitionistic formulation of the machine learning problem, completely
independent from probability theory. Properties of the fuzzy pattern
spaces required for fuzzy inference are demonstrated. |
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Software library for dealing with fuzzy things in Ada
2005. The package includes an implementation of fuzzy sets, fuzzy
logical values, fuzzy numeric values (both integer and floating-point),
linguistic variables, sets of linguistic variables, dimensioned fuzzy numbers
and linguistic variables. |