histMisclassif {RMixtCompUtilities}

Histogram of the misclassification probabilities

Description

Histogram of the misclassification probabilities

Usage

histMisclassif(output, pkg = c("ggplot2", "plotly"), ...)

Arguments

output

object returned by mixtCompLearn function from RMixtComp or rmcMultiRun function from RMixtCompIO

pkg

"ggplot2" or "plotly". Package used to plot

...

arguments to be passed to plot_ly

Details

Missclassification probability of observation i is denoted err_i err_i = 1 - max_k=1,...,K P(Z_i=k|x_i) Histograms of err_i's can be plotted for a specific class, all classes or every class

Author(s)

Matthieu MARBAC

See Also

Other plot: heatmapClass(), heatmapTikSorted(), heatmapVar(), plot.MixtComp(), plotConvergence(), plotDataBoxplot(), plotDataCI(), plotDiscrimClass(), plotDiscrimVar(), plotParamConvergence(), plotProportion()

Examples

if (requireNamespace("RMixtCompIO", quietly = TRUE)) {
  dataLearn <- list(
    var1 = as.character(c(rnorm(50, -2, 0.8), rnorm(50, 2, 0.8))),
    var2 = as.character(c(rnorm(50, 2), rpois(50, 8)))
  )

  model <- list(
    var1 = list(type = "Gaussian", paramStr = ""),
    var2 = list(type = "Poisson", paramStr = "")
  )

  algo <- list(
    nClass = 2,
    nInd = 100,
    nbBurnInIter = 100,
    nbIter = 100,
    nbGibbsBurnInIter = 100,
    nbGibbsIter = 100,
    nInitPerClass = 3,
    nSemTry = 20,
    confidenceLevel = 0.95,
    ratioStableCriterion = 0.95,
    nStableCriterion = 10,
    mode = "learn"
  )

  resLearn <-RMixtCompIO::rmcMultiRun(algo, dataLearn, model, nRun = 3)

  # plot
  histMisclassif(resLearn)
}