Construction of decision trees applying genetic algorithm of structural and parametric synthesis

Shaura А.S., Tenenev V.А.

Abstract


Construction of decision trees is considered as the problem of optimal structural and parametric synthesis. A genetic algorithm is proposed to solve this problem, implementing a consequent trees growing according to the learning dataset. The approach is used for structure encoding based on saving all structural variations in population in the order as they appear. Developed crossing and mutation operators allow avoiding known problems of structural optimization.

Keywords


decision trees; genetic algorithm; structural and parametric optimization; genetic encoding

References References

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Copyright (c) 2012 Александр Сергеевич Шаура, Валентин Алексеевич Тененёв

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ISSN 1813-7911