{
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  "Version": "1.69.0",
  "Title": "MicroArray Gene-expression-based Program In Error rate\nestimation",
  "Author": "Camille Maumet <Rmagpie@gmail.com>, with contributions from C.\nAmbroise J. Zhu",
  "Maintainer": "Camille Maumet <Rmagpie@gmail.com>",
  "Description": "Microarray Classification is designed for both biologists\nand statisticians. It offers the ability to train a classifier\non a labelled microarray dataset and to then use that\nclassifier to predict the class of new observations. A range of\nmodern classifiers are available, including support vector\nmachines (SVMs), nearest shrunken centroids (NSCs)... Advanced\nmethods are provided to estimate the predictive error rate and\nto report the subset of genes which appear essential in\ndiscriminating between classes.",
  "License": "GPL (>= 3)",
  "LazyLoad": "yes",
  "URL": "http://www.bioconductor.org/",
  "biocViews": "Microarray, Classification",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:33:54 UTC",
  "RemoteUrl": "https://github.com/bioc/Rmagpie",
  "RemoteRef": "HEAD",
  "RemoteSha": "01c0eac9e0411bc22e3f0aac9bd69acff5f059b7",
  "NeedsCompilation": "no",
  "Packaged": {
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  "_user": "bioc",
  "_type": "src",
  "_file": "Rmagpie_1.69.0.tar.gz",
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  "_expires": "2027-02-09T17:05:32.000Z",
  "_created": "2026-11-01T14:13:34.000Z",
  "_published": "2026-11-01T17:05:34.401Z",
  "_upstream": "https://github.com/bioc/Rmagpie",
  "_status": "success",
  "_maintainer": {
    "name": "Camille Maumet",
    "email": "rmagpie@gmail.com"
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        "getNoOfRepeats<-",
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        "getResult1LayerCV",
        "getResult1LayerCV,assessment-method",
        "getResult1LayerCV<-",
        "getResult1LayerCV<-,assessment-method",
        "getResult2LayerCV",
        "getResult2LayerCV,assessment-method",
        "getResult2LayerCV<-",
        "getResult2LayerCV<-,assessment-method",
        "getSvmKernel",
        "getSvmKernel,assessment-method",
        "getSvmKernel<-",
        "getSvmKernel<-,assessment-method",
        "getTypeFoldCreation",
        "getTypeFoldCreation,assessment-method",
        "getTypeFoldCreation<-",
        "getTypeFoldCreation<-,assessment-method"
      ]
    },
    {
      "page": "classifyNewSamples-methods",
      "title": "classifyNewSamples Method to classify new samples for a given assessment",
      "topics": [
        "classifyNewSamples",
        "classifyNewSamples,assessment-method",
        "classifyNewSamples-methods"
      ]
    },
    {
      "page": "featureSelectionOptions-class",
      "title": "\"featureSelectionOptions\": A virtual class to store the options of a feature selection",
      "topics": [
        "featureSelectionOptions-class",
        "getOptionValues,featureSelectionOptions-method"
      ]
    },
    {
      "page": "finalClassifier-class",
      "title": "finalClassifier: A class to store the final classifier corresponding to an assessment",
      "topics": [
        "finalClassifier-class",
        "getGenesFromBestToWorst",
        "getGenesFromBestToWorst,finalClassifier-method",
        "getModels",
        "getModels,finalClassifier-method"
      ]
    },
    {
      "page": "findFinalClassifier-methods",
      "title": "findFinalClassifier Method to train and build the final classifier based on an assessment",
      "topics": [
        "findFinalClassifier",
        "findFinalClassifier,assessment-method",
        "findFinalClassifier-methods"
      ]
    },
    {
      "page": "geneSubsets-class",
      "title": "geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection",
      "topics": [
        "geneSubsets-class",
        "getMaxSubsetSize",
        "getMaxSubsetSize,geneSubsets-method",
        "getMaxSubsetSize<-",
        "getMaxSubsetSize<-,geneSubsets-method",
        "getNoModels",
        "getNoModels,geneSubsets-method",
        "getSpeed",
        "getSpeed,geneSubsets-method",
        "getSpeed<-",
        "getSpeed<-,geneSubsets-method",
        "getSubsetsSizes",
        "getSubsetsSizes,geneSubsets-method",
        "getSubsetsSizes<-",
        "getSubsetsSizes<-,geneSubsets-method"
      ]
    },
    {
      "page": "getDataset-methods",
      "title": "getDataset Method to access the attributes of a dataset from an assessment",
      "topics": [
        "getDataset",
        "getDataset,assessment-method",
        "getDataset-methods"
      ]
    },
    {
      "page": "getFeatureSelectionOptions-methods",
      "title": "getFeatureSelectionOptions Method to access the attributes of a featureSelectionOptions from an assessment",
      "topics": [
        "getFeatureSelectionOptions",
        "getFeatureSelectionOptions,assessment-method",
        "getFeatureSelectionOptions-methods"
      ]
    },
    {
      "page": "getFinalClassifier",
      "title": "getFinalClassifier Method to access the attributes of a finalClassifier from an assessment",
      "topics": [
        "getFinalClassifier",
        "getFinalClassifier,assessment-method",
        "getFinalClassifier-methods"
      ]
    },
    {
      "page": "getResults-methods",
      "title": "getResults Method to access the result of one-layer and two-layers cross-validation from an assessment",
      "topics": [
        "getResults",
        "getResults,assessment-method",
        "getResults-methods"
      ]
    },
    {
      "page": "initialize-methods",
      "title": "Initialize objects of class from Rmagpie",
      "topics": [
        "initialize,assessment-method",
        "initialize,geneSubsets-method",
        "initialize,thresholds-method"
      ]
    },
    {
      "page": "plotErrorsFoldTwoLayerCV-methods",
      "title": "plotErrorsFoldTwoLayerCV Method to plot the error rate of a two-layer Cross-validation",
      "topics": [
        "plotErrorsFoldTwoLayerCV",
        "plotErrorsFoldTwoLayerCV,assessment-method",
        "plotErrorsFoldTwoLayerCV-methods"
      ]
    },
    {
      "page": "plotErrorsRepeatedOneLayerCV",
      "title": "plotErrorsRepeatedOneLayerCV Method to plot the estimated error rates in each repeat of a one-layer Cross-validation",
      "topics": [
        "plotErrorsRepeatedOneLayerCV",
        "plotErrorsRepeatedOneLayerCV,assessment-method",
        "plotErrorsRepeatedOneLayerCV-methods"
      ]
    },
    {
      "page": "plotErrorsSummaryOneLayerCV-methods",
      "title": "plotErrorsSummaryOneLayerCV Method to plot the summary estimated error rates of a one-layer Cross-validation",
      "topics": [
        "plotErrorsSummaryOneLayerCV",
        "plotErrorsSummaryOneLayerCV,assessment-method",
        "plotErrorsSummaryOneLayerCV-methods"
      ]
    },
    {
      "page": "rankedGenesImg-methods",
      "title": "rankedGenesImg Method to plot the genes according to their frequency in a microarray like image",
      "topics": [
        "rankedGenesImg",
        "rankedGenesImg,assessment-method",
        "rankedGenesImg-methods"
      ]
    },
    {
      "page": "runOneLayerExtCV-methods",
      "title": "runOneLayerExtCV: Method to run an external one-layer cross-validation",
      "topics": [
        "runOneLayerExtCV",
        "runOneLayerExtCV,assessment-method",
        "runOneLayerExtCV-methods"
      ]
    },
    {
      "page": "runTwoLayerExtCV-methods",
      "title": "runTwoLayerExtCV: Method to run an external two-layers cross-validation",
      "topics": [
        "runTwoLayerExtCV",
        "runTwoLayerExtCV,assessment-method",
        "runTwoLayerExtCV-methods"
      ]
    },
    {
      "page": "setDataset-methods",
      "title": "getDataset<- Method to modify the attributes of a dataset from an assessment",
      "topics": [
        "getDataset<-",
        "getDataset<-,assessment-method",
        "getDataset<--methods"
      ]
    },
    {
      "page": "setFeatureSelectionOptions-methods",
      "title": "getFeatureSelectionOptions<- Method to modify the attributes of a featureSelectionOptions from an assessment",
      "topics": [
        "getFeatureSelectionOptions<-",
        "getFeatureSelectionOptions<-,assessment-method",
        "getFeatureSelectionOptions<--methods"
      ]
    },
    {
      "page": "show-methods",
      "title": "show Display the object, by printing, plotting or whatever suits its class",
      "topics": [
        "show,assessment-method",
        "show,cvErrorRate-method",
        "show,cvErrorRate2ndLayer-method",
        "show,errorRate1stLayerCV-method",
        "show,errorRate2ndLayerCV-method",
        "show,finalClassifier-method",
        "show,frequencyGenes-method",
        "show,frequencyTopGenePerOneModel-method",
        "show,geneSubsets-method",
        "show,result2LayerCV-method",
        "show,resultRepeated1LayerCV-method",
        "show,resultRepeated2LayerCV-method",
        "show,resultSingle1LayerCV-method",
        "show,selectedGenes-method",
        "show,selectedGenes1stLayerCV-method",
        "show,selectedGenes2ndLayerCV-method",
        "show,selectedGenesPerOneOption-method",
        "show,thresholds-method"
      ]
    },
    {
      "page": "thresholds-class",
      "title": "thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid",
      "topics": [
        "getNoThresholds",
        "getNoThresholds,thresholds-method",
        "getNoThresholds<-",
        "getNoThresholds<-,thresholds-method",
        "getOptionValues",
        "getOptionValues,thresholds-method",
        "getOptionValues<-",
        "getOptionValues<-,thresholds-method",
        "thresholds-class"
      ]
    },
    {
      "page": "vV70genes",
      "title": "vV70genes: van't Veer et al. 70 best genes in an object of class dataset.",
      "topics": [
        "vV70genes"
      ]
    }
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      "headings": [],
      "created": "2013-11-01 20:08:44",
      "modified": "2013-11-02 23:14:58",
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