Abstract: Examples described herein relate to generation of radio frequency (RF) plans for network deployments. Examples described herein may receive an input RF plan with modified set of features of a network deployment area. A first machine learning (ML) model generates an intermediate RF plan indicating candidate AR locations based on the modified set of features and a first set of parameters. A second ML model determines a network optimization score for the intermediate RF plan. Based on the optimization score, the first set of parameters are optimized. The first ML model generates an output RF plan indicating optimized AP locations based on the optimized first set of parameters and the modified set of features.