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Learning from imprecise examples with GA-P algorithms.

Luciano SánchezInés Couso — 1998

Mathware and Soft Computing

GA-P algorithms combine genetic programming and genetic algorithms to solve symbolic regression problems. In this work, we will learn a model by means of an interval GA-P procedure which can use precise or imprecise examples. This method provides us with an analytic expression that shows the dependence between input and output variables, using interval arithmetic. The method also provides us with interval estimations of the parameters on which this expression depends. The algorithm that...

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