In the clustering analysis,three-way k-means clustering algorithm has a great improvement over the traditional k-means clustering algorithm.The algorithm has a strong ability to deal with data with uncertain boundary.However,it is still sensitive to the initial clustering center.By combining ant colony algorithm and three-way k-means clustering algorithm,this paper presents a three-way k-means clustering algorithm based on ant colony algorithm to solve this problem.Using the random probability selection strategy in ant colony algorithm and the positive and negative feedback mechanism of pheromone,the weight is dynamically adjusted to optimize the three k-means clustering algorithms.Experiments show that this method improves the performance index of clustering results.The effectiveness of the algorithm is verified on UCI data set.
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