Type Hierarchy and State

Internal storage conventions and model types. Public base types are documented under Advanced configuration.

Index

Model Types

SingleART

AdaptiveResonance.SingleART — Type
abstract type SingleART <: ART

Summary

Abstract supertype of single ART modules with matrix weights and symbol-based activation, match, and update functions.

Fields

source

AbstractFuzzyART

MergeART

AdaptiveResonance.MergeART — Type
mutable struct MergeART <: ART

Summary

MergeART module struct.

For module options, see AdaptiveResonance.opts_MergeART.

References

  1. L. E. Brito da Silva, I. Elnabarawy, and D. C. Wunsch, 'Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence,' Neural Networks, vol. 121, pp. 208-228, 2020, doi: 10.1016/j.neunet.2019.08.033.
  2. G. Carpenter, S. Grossberg, and D. Rosen, 'Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system,' Neural Networks, vol. 4, no. 6, pp. 759-771, 1991.

Fields

  • opts::opts_DDVFA: DDVFA options struct.
  • subopts::opts_FuzzyART: FuzzyART options struct used for all F2 nodes.
  • config::DataConfig: Data configuration struct.
  • threshold::Float64: Operating module threshold value, a function of the vigilance parameter.
  • F2::Vector{FuzzyART}: List of F2 nodes (themselves FuzzyART modules).
  • labels::Vector{Int64}: Incremental list of labels corresponding to each F2 node, self-prescribed or supervised.
  • n_categories::Int64: Number of total categories.
  • epoch::Int64: Current training epoch.
  • T::Vector: DDVFA activation values.
  • M::Vector: DDVFA match values.
  • stats::Dict{String, Any}: Runtime statistics for the module, implemented as a dictionary containing entries at the end of each training iteration. These entries include the best-matching unit index and the activation and match values of the winning node.
source

opts_MergeART

AdaptiveResonance.opts_MergeART — Type
mutable struct opts_MergeART <: ARTOpts

Summary

MergeART options struct.

These options are a Parameters.jl struct, taking custom options keyword arguments. Each field has a default value listed below.

Fields

  • match_tracking::Bool: Flag to enable match tracking. Default: false

  • epsilon::Float64: Positive match-tracking increment: episilon ∈ (0, 1) Default: 0.001

  • rho_lb::Float64: Lower-bound vigilance parameter: rho_lb ∈ [0, 1]. Default: 0.7

  • rho_ub::Float64: Upper bound vigilance parameter: rho_ub ∈ [0, 1]. Default: 0.85

  • alpha::Float64: Choice parameter: alpha > 0. Default: 0.001

  • beta::Float64: Learning parameter: beta ∈ (0, 1]. Default: 1.0

  • gamma::Float64: Pseudo kernel width: gamma >= 1. Default: 3.0

  • gamma_ref::Float64: Reference gamma for normalization: 0 <= gamma_ref < gamma. Default: 1.0

  • similarity::Symbol: Similarity method (activation and match): similarity ∈ [:single, :average, :complete, :median, :weighted, :centroid]. Default: :single

  • max_epoch::Int64: Maximum number of epochs during training: max_epochs ∈ (1, Inf). Default: 1

  • display::Bool: Display flag for progress bars. Default: false

  • gamma_normalization::Bool: Flag to normalize the threshold by the feature dimension. Default: true

  • uncommitted::Bool: Flag to use an uncommitted node when learning.

    If true, new weights are created with ones(dim) and learn on the complement-coded sample. If false, fast-committing is used where the new weight is simply the complement-coded sample. Default: false

  • activation::Symbol: Selected activation function. Default: :gamma_activation

  • match::Symbol: Selected match function. Default: :gamma_match

  • update::Symbol: Selected weight update function. Default: :basic_update

  • sort::Bool: Flag to sort the F2 nodes by activation before the match phase

    When true, the F2 nodes are sorted by activation before match. When false, an iterative argmax and inhibition procedure is used to find the best-matching unit. Default: false

source

Storage and Dimensions

ARTMatrix

ARTVector

ARTStats

AdaptiveResonance.ARTStats — Type

ARTStats

Description

Definition of the ART module statistics dictionary, used to generate and store various logs during training and testing.

source

ARTIterator

ART_DIM

ART_SAMPLES