## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- library(micer) ## ----------------------------------------------------------------------------- data(mcData) miceResultMC <- mice(mcData$ref, mcData$pred, mappings=c("Barren", "Forest", "Impervious", "Low Vegetation", "Mixed Dev", "Water"), multiclass=TRUE) cmMC <- table(mcData$pred, mcData$ref) miceResultMC <- miceCM(cmMC, mappings=c("Barren", "Forest", "Impervious", "Low Vegetation", "Mixed Dev", "Water"), multiclass=TRUE) print(miceResultMC) ## ----------------------------------------------------------------------------- data(biData) miceResultBI <- mice(biData$ref, biData$pred, mappings = c("Mined", "Not Mined"), multiclass=FALSE, positiveIndex=1) cmB <- table(biData$pred, biData$ref) miceResultBI <- miceCM(cmB, mappings=c("Mined", "Not Mined"), multiclass=FALSE, positiveIndex=1) print(miceResultBI) ## ----------------------------------------------------------------------------- data(mcData) ciResultsMC <- miceCI(rep=1000, frac=.7, mcData$ref, mcData$pred, lowPercentile=0.025, highPercentile=0.975, mappings=c("Barren", "Forest", "Impervious", "Low Vegetation", "Mixed Dev", "Water"), multiclass=TRUE) print(ciResultsMC) ## ----------------------------------------------------------------------------- data(biData) ciResultsBi <- miceCI(rep=1000, frac=.7, biData$ref, biData$pred, lowPercentile=0.025, highPercentile=0.975, mappings = c("Mined", "Not Mined"), multiclass=FALSE, positiveIndex=1) print(ciResultsBi) ## ----------------------------------------------------------------------------- data(compareData) set.seed(42) compareResult <- miceCompare(ref=compareData$ref, result1=compareData$rfPred, result2=compareData$dtPred, reps=1000, frac=.7) print(compareResult)