About FID

FID builds a fuzzy decision tree with several options for processing. Key features include:

  • fuzzy-set based and exemplar-based inferences
  • fuzzifying unrecognisable data to force classification
  • choice of multiple norms, with the ability of selecting the best for given data
  • processing nominal, fuzzy, and ordered symbolic data
  • ability to deal with missing or noisy features, both in training and in data classification
  • two discretization methods for unpartitioned continuous domains
    1. top-down data-driven selective discretization
    2. bottom-up data-driven global discretization
  • k-fold cross-validation
  • artificial noise and missing value induction
  • tree pruning

FID 3.5

Current Version - Released August 2015

  • upgrade to 3.4
  • added ability to induce artificial noise and missing values into datasets
  • added k-fold cross validation
  • recompiled and tested on current versions of Windows, Linux, and Unix (OS X is in the works)
  • GUI updated and tested
  • user manual updated
  • minor bug fixes

FID 4.0

  • Fuzzy Decision Forest plus built-in cross validation
  • currently not available

FID 3.4

  • GUI interface added
  • redone inferences
  • redone top-down partitioning with additional parameter
  • fixed bottom-up partitioning
  • added pruning
  • improved user manual
  • minor bug fixes

FID 3.3

  • debugged and modified top-down discretization
  • added bottom-up discretization
  • improved treatment of examples with missing features
  • improved parameters

FID 2.1

  • fixed treatment of examples with missing features
  • renamed and redefined minInfPkN parameter

FID 2.0

  • the first version made available in 1997