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

Date

2019-10-20

Author

İyigün, Cem

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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

URI

https://hdl.handle.net/11511/86852
https://cdn2.hubspot.net/hubfs/3449182/2019_INFORMS_Annual_Meeting_Back_Matter.pdf?__hstc=194041586.afeadd9fe7b3b16cc4b18d0f05894a05.1613646625948.1613646625948.1613646625948.1&__hssc=194041586.3.1613646625951&hsCtaTracking=820e16f1-b6bc-4fc7-bdf4-87cae6d9bfaf%7C3f517cf7-0c21-47b0-a192-5cd115cf9349

Conference Name

Informs Annual Meeting , October 20-23 2019

Collections

Department of Industrial Engineering, Conference / Seminar

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Citation Formats

C. İyigün, “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.