Mixed integer programming and heuristics approaches for clustering with cluster-based feature selection

2019-10-20
İyigün, Cem
Onen Oz, Sena
In this study, we work on a clustering problem where it is assumed that the features identifying the clusters may differ for each cluster. Number of clusters and number of relevant features in each cluster are given in advance. A centerbased clustering approach is proposed. Finding the cluster centers, assigning the data points and selecting relevant features for each cluster are performed simultaneously. A non-linear mixed integer mathematical model is proposed which minimizes the total distance between data points and their cluster center by using the selected features for each cluster. Different linearization methods have been used for solving the problem. Besides, two different heuristic algorithms have been developed by taking into account the nature of the mentioned problem. Experimental results have been presented
Citation Formats
C. İyigün and S. Onen Oz, “Mixed integer programming and heuristics approaches for clustering with cluster-based feature selection,” presented at the Informs Annual Meeting , October 20-23 2019, Washington, USA, 2019, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/86852.