Clusters: private API
PortfolioOptimisers.AbstractClustersEstimator — Type
abstract type AbstractClustersEstimator <: AbstractPhylogenyEstimatorAbstract supertype for all clustering estimator types.
All concrete and/or abstract types implementing clustering-based estimation algorithms should be subtypes of AbstractClustersEstimator.
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PortfolioOptimisers.AbstractClustersAlgorithm — Type
abstract type AbstractClustersAlgorithm <: AbstractPhylogenyAlgorithmAbstract supertype for all clustering algorithm types.
All concrete and/or abstract types implementing specific clustering algorithms should be subtypes of AbstractClustersAlgorithm.
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PortfolioOptimisers.AbstractHierarchicalClusteringAlgorithm — Type
abstract type AbstractHierarchicalClusteringAlgorithm <: AbstractClustersAlgorithmAbstract supertype for all hierarchical clustering algorithm types.
All concrete and/or abstract types implementing hierarchical clustering algorithms (such as hierarchical agglomerative clustering or DBHT) should be subtypes of AbstractHierarchicalClusteringAlgorithm.
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PortfolioOptimisers.AbstractNonHierarchicalClusteringAlgorithm — Type
abstract type AbstractNonHierarchicalClusteringAlgorithm <: AbstractClustersAlgorithmAbstract supertype for all non-hierarchical clustering algorithm types.
All concrete and/or abstract types implementing non-hierarchical clustering algorithms (such as k-means) should be subtypes of AbstractNonHierarchicalClusteringAlgorithm.
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PortfolioOptimisers.AbstractOptimalNumberClustersEstimator — Type
abstract type AbstractOptimalNumberClustersEstimator <: AbstractEstimatorAbstract supertype for all optimal number of clusters estimator types.
All concrete and/or abstract types implementing algorithms to estimate the optimal number of clusters should be subtypes of AbstractOptimalNumberClustersEstimator.
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PortfolioOptimisers.AbstractOptimalNumberClustersAlgorithm — Type
abstract type AbstractOptimalNumberClustersAlgorithm <: AbstractAlgorithmAbstract supertype for all optimal number of clusters algorithm types.
All concrete and/or abstract types implementing specific algorithms for determining the optimal number of clusters should be subtypes of AbstractOptimalNumberClustersAlgorithm.
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PortfolioOptimisers.AbstractClusteringResult — Type
abstract type AbstractClusteringResult <: AbstractPhylogenyResultAbstract supertype for all clustering result types.
All concrete and/or abstract types representing the result of a clustering estimation should be subtypes of AbstractClusteringResult.
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PortfolioOptimisers.Int_ONC — Type
const Int_ONC = Union{<:Integer, <:AbstractOptimalNumberClustersAlgorithm}Alias for an integer or optimal number of clusters algorithm.
Matches either a plain integer (specifying the number of clusters directly) or an AbstractOptimalNumberClustersAlgorithm (which determines the optimal number automatically).
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PortfolioOptimisers.ClTypes — Type
const ClTypes = Union{<:Clustering.ClusteringResult, <:Clustering.Hclust}Alias for clustering result types from the Clustering.jl package.
Matches either a Clustering.ClusteringResult or Clustering.Hclust. Used internally to accept output from the Clustering.jl library for both flat and hierarchical clustering results.
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PortfolioOptimisers.ClE_Cl — Type
const ClE_Cl = Union{<:AbstractClustersEstimator, <:AbstractClusteringResult}Alias for a clustering estimator or result.
Matches either an AbstractClustersEstimator or an AbstractClusteringResult. Used for dispatch in phylogeny and network estimation workflows that accept either form.
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