CLUSTERING ANALYSIS USING A SELF-ORGANIZED NETWORK INSPIRED BY IMMUNE ALGORITHM

摘要

An automatic construction of neurons in neural network inspired by immune algorithm is proposed. The new network is combined with the contiguity-constrained method to perform clustering analysis. The applicability of this technique is tested with two widely referenced machine-learning cases. The experiment shows that the new technique achieved 99.33% and 100% correctness for his plant data and Wine recognition data respectively, better than other popular clustering methods.