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Presented at the 2022 IEEE Region 10 Conference (TENCON 2022). Our main contribution is twofold: (1) the construction of a meta-learning model for recommending a distance metric for k-means clustering and (2) a fine-grained analysis of the importance and effects of the meta-features on the model's output