Dependency aware feature selection is a simple but effective method proposed in Somol, Petr, Jiří Grim, and Pavel Pudil. "Fast dependency-aware feature selection in very-high-dimensional pattern recognition." 2011 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, 2011.. The method is realated to Shapley values (https://en.wikipedia.org/wiki/Shapley_value) and hence to explanation methods based on this GT concept Kononenko, Igor. "An efficient explanation of individual classifications using game theory." Journal of Machine Learning Research 11.Jan (2010): 1-18.
- Popularity
- 4 Stars
- Updated Last
- 4 Years Ago
- Started In
- November 2018
Required Packages
- 
        
          Accessors
- 
        
          AliasTables
- 
        
          ChainRulesCore
- 
        
          ChangesOfVariables
- 
        
          Combinatorics
- 
        
          CommonSolve
- 
        
          Compat
- 
        
          CompositionsBase
- 
        
          ConstructionBase
- 
        
          DataAPI
- 
        
          DataStructures
- 
        
          DensityInterface
- 
        
          Distributions
- 
        
          DocStringExtensions
- 
        
          FillArrays
- 
        
          HypergeometricFunctions
- 
        
          HypothesisTests
- 
        
          InverseFunctions
- 
        
          IrrationalConstants
- 
        
          LogExpFunctions
- 
        
          MacroTools
- 
        
          Missings
- 
        
          OrderedCollections
- 
        
          PDMats
- 
        
          PtrArrays
- 
        
          QuadGK
- 
        
          Reexport
- 
        
          Requires
- 
        
          Rmath
- 
        
          Roots
- 
        
          SortingAlgorithms
- 
        
          SparseArrays
- 
        
          SpecialFunctions
- 
        
          StatsAPI
- 
        
          StatsBase
- 
        
          StatsFuns
Used By Packages
No packages found.