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  "Authors@R": "c(\nperson(family=\"Maxwell\", given=\"Aaron\", email=\"Aaron.Maxwell@mail.wvu.edu\", role=c(\"aut\", \"cre\", \"cph\")),\nperson(family=\"Farhadpour\", given=\"Sarah\", email=\"sf00039@mix.wvu.edu\", role=c(\"aut\")))",
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  "Description": "Map image classification efficacy (MICE) adjusts the\naccuracy rate relative to a random classification baseline\n(Shao et al. (2021)<doi:10.1109/ACCESS.2021.3116526> and Tang\net al. (2024)<doi:10.1109/TGRS.2024.3446950>). Only the\nproportions from the reference labels are considered, as\nopposed to the proportions from the reference and predictions,\nas is the case for the Kappa statistic. This package offers\nmeans to calculate MICE and adjusted versions of class-level\nuser's accuracy (i.e., precision) and producer's accuracy\n(i.e., recall) and F1-scores. Class-level metrics are\naggregated using macro-averaging. Functions are also made\navailable to estimate confidence intervals using bootstrapping\nand statistically compare two classification results.",
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