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Fuzzy machine learning framework to run in Windows online

Free download Fuzzy machine learning framework to run in Windows online over Linux online Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named Fuzzy machine learning framework to run in Windows online over Linux online whose latest release can be downloaded as fuzzy_ml_1_10.tgz. It can be run online in the free hosting provider OnWorks for workstations.

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- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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Fuzzy machine learning framework to run in Windows online over Linux online


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 or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.

Features

  • Based on the intuitionistic fuzzy sets and the possibility theory
  • All the data the system operates on are considered fuzzy
  • Fuzzy classes, within the framework classes take a natural interpretation of distinguished features
  • Numeric, enumeration features and features based on linguistic variables
  • Open for definition of new features beyond built-in classes of numeric, nominal and linguistic ones
  • Derived and evaluated features. Along with the measured features the system supports the features deduced from other features
  • Classifiers as features for building hierarchical systems
  • Automatic refinement in case of dependent features
  • Incremental learning support
  • Extended fuzzy control language support
  • Object-oriented software design
  • Features, training sets and classifiers are extensible objects
  • Automatic garbage collection
  • Generic data base support through ODBC and SQLite
  • Ada 95, 2005, 2012 compliant. GTK+ GUI requires at least Ada 2005
  • Text I/O is provided for teaching sets and classifiers. Teaching sets can be imported in an intuitive format from text files
  • Training sets and classifiers can be output in directly HTML format, supporting a web-ready solution
  • GTK+ 3 GUI. The GUI is optional the system can be used fully programmatically
  • Delivered with an set of samples varying from ones illustrating usage of the system components to examples of training on real- life and size data


Audience

Science/Research, Education, Advanced End Users, Developers


User interface

GTK+


Programming Language

Ada


Database Environment

SQLite, ODBC


This is an application that can also be fetched from https://sourceforge.net/projects/fuzzyml/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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