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Despite self-organizing networks (SONs) pursue the automation of management tasks in current cellular networks, the selection of the most useful performance indicators (PIs), used as inputs for SON functions, is still performed by network experts. In this letter, a novel supervised technique for the automatic selection of PIs for self-healing functions is proposed, relying on the dissimilarity of their statistical behavior under different network states. Results using data from a live networkdoi:10.1109/lcomm.2018.2825392 fatcat:wsrdm37x6fbjxoio4324tk7cwy