Abstract: We propose a novel method for regression tree induction based on modeling ant foraging behavior, combining techniques from both traditional regression tree induction algorithms and ant algorithms. The results of experiments on publicly available data sets show that the proposed method outperforms conventional algorithms for regression tree induction in accuracy and results in less complex solutions.
Keywords: machine learning, non-linear regression, piecewise linear regression, regression trees, model trees, ant algorithms, ant colony optimization
Authors and copyright holders:
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For citation:
Melnikov G. A., Gubarev V. V. Method for regression tree induction based on the ant algorithms. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2014, no. 4(34), pp. 72–78.
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