Ant colony optimization and decision function estimation
Hadi Shahraki, Seyed-Hamid Zahiri · Intelligent Decision Technologies · 2016
In this paper a new classifier based on ant colony optimization in continuous domains (ACOR) has been proposed. In this classifier, ACOR is used to find the decision hyperplanes between the different classes. Also, a new cost function is proposed to find maximum-margin hyperplanes. The effectivenes s of proposed classifier is evaluated by some common benchmarks with different feature space dimensions and number of classes. Also the performance of proposed classifier is compared with some of the conventional, heuristic and ACO-based classifier. The experimental results show that the performance of proposed classifier is comparable and sometimes better than compared classifiers.