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Optimal Classification/Rypka/Equations/Separatory/Characteristic/Empirical/Separation

< Optimal Classification | Rypka | Equations | Separatory

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Separation StagesEdit

Initial separation Edit

 S_j = \frac{\left[(G^{2})-\sum_{l=0}^{R} n_l^{2}\right]}{2}, where:[1]

  • Sj is the initial empirical separatory value for each characteristic, where,
j = 0...C and is the index of the jth characteristic in the group and C is the number of characteristics in the group, and,
l = 0...R and is the truth table value of the jth characteristic, where R is the truth table size, where:
R = V0, and,
  • V is the highest value of logic in the group and,
  • 0 is the target set exponent for a single characteristic, and,
  • G is the number of elements in the bounded class.

Subsequent separation Edit

 S = \frac{\left[(G^{2})-\sum_{l=0}^{R} n_l^{2}\right]}{2}, where:

  • Sj is the initial empirical separatory value for each characteristic, where,
l = 0...R and is the target set truth table index value, where R is the target set truth table size value, where:
R = VK, and,
  • V is the highest value of logic in the group and,
  • K is the number of characteristics in the target set, and,
  • G is the number of elements in the bounded class.

Notes Edit

  1. Must be applied initially to each characteristic. (The equations have been implemented in Mathcad and using the Visual Basic programming language. See Application_Example

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