Abstract
In this paper we present CIDIM (Control of Induction by sample DIvision Method), an algorithm that has been developed to induce small and accurate decision trees using a set of examples. It uses an internal control of induction to stop the induction and to avoid the overfitting. Other ideas like a dichotomic division or groups of consecutive values are used to improve the performance of the algorithm. CIDIM has been successfully compared with ID3 and C4.5. It induces trees that are significantly better than those induced by ID3 or C4.5 in almost every experiment.
This work has been partially supported by the MOISES project, number TIC2002-04019-C03-02, of the MCyT, Spain.
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Ramos-Jiménez, G., del Campo-Ávila, J., Morales-Bueno, R. (2005). Induction of Decision Trees Using an Internal Control of Induction. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_97
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DOI: https://doi.org/10.1007/11494669_97
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