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AUTOMATICALLY REDUCING MACHINE LEARNING MODEL INPUTS

Abstract:

Various embodiments are generally directed to techniques to reduce inputs of a machine learning model (MLM) and increase path efficiency as a result. A method for reducing an MLM includes: receiving a machine learning (ML) dataset, partitioning the ML dataset into a first dataset, a second dataset, a third dataset, and a fourth dataset, training, validating, and testing the MLM using one or more of the first dataset, the second dataset, and the third dataset, after testing the MLM, automatically ranking an importance associated with each input of the MLM using the fourth dataset, and reducing a plurality of inputs of the MLM based on the automatic ranking.