Package facebook4j

Examples of facebook4j.Question$Option

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    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();
   
    Option dataOpt = obuilder.withLongName("data").withShortName("d").withRequired(true)
        .withArgument(abuilder.withName("path").withMinimum(1).withMaximum(1).create())
        .withDescription("Data path").create();
   
    Option datasetOpt = obuilder.withLongName("dataset").withShortName("ds").withRequired(true)
        .withArgument(abuilder.withName("dataset").withMinimum(1).withMaximum(1).create())
        .withDescription("Dataset path").create();
   
    Option selectionOpt = obuilder.withLongName("selection").withShortName("sl").withRequired(false)
        .withArgument(abuilder.withName("m").withMinimum(1).withMaximum(1).create())
        .withDescription("Optional, Number of variables to select randomly at each tree-node.\n" +
        "For classification problem, the default is square root of the number of explanatory variables.\n" +
        "For regression problem, the default is 1/3 of the number of explanatory variables.").create();

    Option noCompleteOpt = obuilder.withLongName("no-complete").withShortName("nc").withRequired(false)
        .withDescription("Optional, The tree is not complemented").create();

    Option minSplitOpt = obuilder.withLongName("minsplit").withShortName("ms").withRequired(false)
        .withArgument(abuilder.withName("minsplit").withMinimum(1).withMaximum(1).create())
        .withDescription("Optional, The tree-node is not divided, if the branching data size is " +
        "smaller than this value.\nThe default is 2.").create();

    Option minPropOpt = obuilder.withLongName("minprop").withShortName("mp").withRequired(false)
        .withArgument(abuilder.withName("minprop").withMinimum(1).withMaximum(1).create())
        .withDescription("Optional, The tree-node is not divided, if the proportion of the " +
        "variance of branching data is smaller than this value.\n" +
        "In the case of a regression problem, this value is used. " +
        "The default is 1/1000(0.001).").create();

    Option seedOpt = obuilder.withLongName("seed").withShortName("sd").withRequired(false)
        .withArgument(abuilder.withName("seed").withMinimum(1).withMaximum(1).create())
        .withDescription("Optional, seed value used to initialise the Random number generator").create();
   
    Option partialOpt = obuilder.withLongName("partial").withShortName("p").withRequired(false)
        .withDescription("Optional, use the Partial Data implementation").create();
   
    Option nbtreesOpt = obuilder.withLongName("nbtrees").withShortName("t").withRequired(true)
        .withArgument(abuilder.withName("nbtrees").withMinimum(1).withMaximum(1).create())
        .withDescription("Number of trees to grow").create();
   
    Option outputOpt = obuilder.withLongName("output").withShortName("o").withRequired(true)
        .withArgument(abuilder.withName("path").withMinimum(1).withMaximum(1).create())
        .withDescription("Output path, will contain the Decision Forest").create();

    Option helpOpt = obuilder.withLongName("help").withShortName("h")
        .withDescription("Print out help").create();
   
    Group group = gbuilder.withName("Options").withOption(dataOpt).withOption(datasetOpt)
        .withOption(selectionOpt).withOption(noCompleteOpt).withOption(minSplitOpt)
        .withOption(minPropOpt).withOption(seedOpt).withOption(partialOpt).withOption(nbtreesOpt)
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  public static void main(String[] args) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option seqOpt = obuilder.withLongName("seqFile").withRequired(false).withArgument(
            abuilder.withName("seqFile").withMinimum(1).withMaximum(1).create()).withDescription(
            "The Sequence File containing the Vectors").withShortName("s").create();
    Option vectorAsKeyOpt = obuilder.withLongName("useKey").withRequired(false).withDescription(
            "If the Key is a vector, then dump that instead").withShortName("u").create();
    Option printKeyOpt = obuilder.withLongName("printKey").withRequired(false).withDescription(
            "Print out the key as well, delimited by a tab (or the value if useKey is true)").withShortName("p")
            .create();
    Option outputOpt = obuilder.withLongName("output").withRequired(false).withArgument(
        abuilder.withName("output").withMinimum(1).withMaximum(1).create()).withDescription(
            "The output file.  If not specified, dumps to the console").withShortName("o").create();
    Option dictOpt = obuilder.withLongName("dictionary").withRequired(false).withArgument(
        abuilder.withName("dictionary").withMinimum(1).withMaximum(1).create()).withDescription(
            "The dictionary file. ").withShortName("d").create();
    Option dictTypeOpt = obuilder.withLongName("dictionaryType").withRequired(false).withArgument(
            abuilder.withName("dictionaryType").withMinimum(1).withMaximum(1).create()).withDescription(
            "The dictionary file type (text|sequencefile)").withShortName("dt").create();
    Option csvOpt = obuilder.withLongName("csv").withRequired(false).withDescription(
            "Output the Vector as CSV.  Otherwise it substitutes in the terms for vector cell entries")
            .withShortName("c").create();
    Option namesAsCommentsOpt = obuilder.withLongName("namesAsComments").withRequired(false).withDescription(
            "If using CSV output, optionally add a comment line for each NamedVector (if the vector is one) printing out the name")
            .withShortName("n").create();
    Option sortVectorsOpt = obuilder.withLongName("sortVectors").withRequired(false).withDescription(
            "Sort output key/value pairs of the vector entries in abs magnitude descending order")
            .withShortName("sort").create();
    Option sizeOpt = obuilder.withLongName("sizeOnly").withRequired(false).
            withDescription("Dump only the size of the vector").withShortName("sz").create();
    Option numItemsOpt = obuilder.withLongName("numItems").withRequired(false).withArgument(
        abuilder.withName("n").withMinimum(1).withMaximum(1).create()).
            withDescription("Output at most <n> vecors").withShortName("n").create();
    Option numIndexesPerVectorOpt = obuilder.withLongName("vectorSize").withShortName("vs")
        .withRequired(false).withArgument(abuilder.withName("vs").withMinimum(1)
                                              .withMaximum(1).create())
        .withDescription("Truncate vectors to <vs> length when dumping (most useful when in"
                             + " conjunction with -sort").create();
    Option filtersOpt = obuilder.withLongName("filter").withRequired(false).withArgument(
            abuilder.withName("filter").withMinimum(1).withMaximum(100).create()).
            withDescription("Only dump out those vectors whose name matches the filter." +
            "  Multiple items may be specified by repeating the argument.").withShortName("fi").create();
    Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h")
            .create();

    Group group = gbuilder.withName("Options").withOption(seqOpt).withOption(outputOpt)
                          .withOption(dictTypeOpt).withOption(dictOpt).withOption(csvOpt)
                          .withOption(vectorAsKeyOpt).withOption(printKeyOpt).withOption(sortVectorsOpt)
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  public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = DefaultOptionCreator.inputOption().create();

    Option labelOpt = obuilder.withLongName("label").withRequired(true).withShortName("l")
        .withArgument(abuilder.withName("index").withMinimum(1).withMaximum(1).create())
        .withDescription("label's index.").create();

    Option thresholdOpt = obuilder.withLongName("threshold").withRequired(false).withShortName("t").withArgument(
        abuilder.withName("threshold").withMinimum(1).withMaximum(1).create()).withDescription(
        "Condition activation threshold, default = 0.5.").create();

    Option crosspntsOpt = obuilder.withLongName("crosspnts").withRequired(false).withShortName("cp").withArgument(
        abuilder.withName("points").withMinimum(1).withMaximum(1).create()).withDescription(
        "Number of crossover points to use, default = 1.").create();

    Option mutrateOpt = obuilder.withLongName("mutrate").withRequired(true).withShortName("m").withArgument(
        abuilder.withName("true").withMinimum(1).withMaximum(1).create())
        .withDescription("Mutation rate (float).").create();

    Option mutrangeOpt = obuilder.withLongName("mutrange").withRequired(false).withShortName("mr").withArgument(
        abuilder.withName("range").withMinimum(1).withMaximum(1).create())
        .withDescription("Mutation range, default = 0.1 (10%).").create();

    Option mutprecOpt = obuilder.withLongName("mutprec").withRequired(false).withShortName("mp").withArgument(
        abuilder.withName("precision").withMinimum(1).withMaximum(1).create())
        .withDescription("Mutation precision, default = 2.").create();

    Option popsizeOpt = obuilder.withLongName("popsize").withRequired(true).withShortName("p").withArgument(
        abuilder.withName("size").withMinimum(1).withMaximum(1).create()).withDescription("Population size.").create();

    Option gencntOpt = obuilder.withLongName("gencnt").withRequired(true).withShortName("g").withArgument(
        abuilder.withName("count").withMinimum(1).withMaximum(1).create())
        .withDescription("Generations count.").create();

    Option helpOpt = DefaultOptionCreator.helpOption();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(helpOpt).withOption(labelOpt)
        .withOption(thresholdOpt).withOption(crosspntsOpt).withOption(mutrateOpt).withOption(mutrangeOpt)
        .withOption(mutprecOpt).withOption(popsizeOpt).withOption(gencntOpt).create();
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  public static int main2(String[] args, Configuration conf) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option helpOpt = DefaultOptionCreator.helpOption();

    Option inputDirOpt = obuilder.withLongName("input").withRequired(true).withArgument(
      abuilder.withName("input").withMinimum(1).withMaximum(1).create()).withDescription(
      "The Directory on HDFS containing the collapsed, properly formatted files having "
          + "one doc per line").withShortName("i").create();

    Option dictOpt = obuilder.withLongName("dictionary").withRequired(false).withArgument(
      abuilder.withName("dictionary").withMinimum(1).withMaximum(1).create()).withDescription(
      "The path to the term-dictionary format is ... ").withShortName("d").create();

    Option dfsOpt = obuilder.withLongName("dfs").withRequired(false).withArgument(
      abuilder.withName("dfs").withMinimum(1).withMaximum(1).create()).withDescription(
      "HDFS namenode URI").withShortName("dfs").create();

    Option numTopicsOpt = obuilder.withLongName("numTopics").withRequired(true).withArgument(abuilder
        .withName("numTopics").withMinimum(1).withMaximum(1)
        .create()).withDescription("Number of topics to learn").withShortName("top").create();

    Option outputTopicFileOpt = obuilder.withLongName("topicOutputFile").withRequired(true).withArgument(
        abuilder.withName("topicOutputFile").withMinimum(1).withMaximum(1).create())
        .withDescription("File to write out p(term | topic)").withShortName("to").create();

    Option outputDocFileOpt = obuilder.withLongName("docOutputFile").withRequired(true).withArgument(
        abuilder.withName("docOutputFile").withMinimum(1).withMaximum(1).create())
        .withDescription("File to write out p(topic | docid)").withShortName("do").create();

    Option alphaOpt = obuilder.withLongName("alpha").withRequired(false).withArgument(abuilder
        .withName("alpha").withMinimum(1).withMaximum(1).withDefault("0.1").create())
        .withDescription("Smoothing parameter for p(topic | document) prior").withShortName("a").create();

    Option etaOpt = obuilder.withLongName("eta").withRequired(false).withArgument(abuilder
        .withName("eta").withMinimum(1).withMaximum(1).withDefault("0.1").create())
        .withDescription("Smoothing parameter for p(term | topic)").withShortName("e").create();

    Option maxIterOpt = obuilder.withLongName("maxIterations").withRequired(false).withArgument(abuilder
        .withName("maxIterations").withMinimum(1).withMaximum(1).withDefault(10).create())
        .withDescription("Maximum number of training passes").withShortName("m").create();

    Option modelCorpusFractionOption = obuilder.withLongName("modelCorpusFraction")
        .withRequired(false).withArgument(abuilder.withName("modelCorpusFraction").withMinimum(1)
        .withMaximum(1).withDefault(0.0).create()).withShortName("mcf")
        .withDescription("For online updates, initial value of |model|/|corpus|").create();

    Option burnInOpt = obuilder.withLongName("burnInIterations").withRequired(false).withArgument(abuilder
        .withName("burnInIterations").withMinimum(1).withMaximum(1).withDefault(5).create())
        .withDescription("Minimum number of iterations").withShortName("b").create();

    Option convergenceOpt = obuilder.withLongName("convergence").withRequired(false).withArgument(abuilder
        .withName("convergence").withMinimum(1).withMaximum(1).withDefault("0.0").create())
        .withDescription("Fractional rate of perplexity to consider convergence").withShortName("c").create();

    Option reInferDocTopicsOpt = obuilder.withLongName("reInferDocTopics").withRequired(false)
        .withArgument(abuilder.withName("reInferDocTopics").withMinimum(1).withMaximum(1)
        .withDefault("no").create())
        .withDescription("re-infer p(topic | doc) : [no | randstart | continue]")
        .withShortName("rdt").create();

    Option numTrainThreadsOpt = obuilder.withLongName("numTrainThreads").withRequired(false)
        .withArgument(abuilder.withName("numTrainThreads").withMinimum(1).withMaximum(1)
        .withDefault("1").create())
        .withDescription("number of threads to train with")
        .withShortName("ntt").create();

    Option numUpdateThreadsOpt = obuilder.withLongName("numUpdateThreads").withRequired(false)
        .withArgument(abuilder.withName("numUpdateThreads").withMinimum(1).withMaximum(1)
        .withDefault("1").create())
        .withDescription("number of threads to update the model with")
        .withShortName("nut").create();

    Option verboseOpt = obuilder.withLongName("verbose").withRequired(false)
        .withArgument(abuilder.withName("verbose").withMinimum(1).withMaximum(1)
        .withDefault("false").create())
        .withDescription("print verbose information, like top-terms in each topic, during iteration")
        .withShortName("v").create();
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  }

  public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = DefaultOptionCreator.inputOption().create();

    Option helpOpt = DefaultOptionCreator.helpOption();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(helpOpt).create();

    Parser parser = new Parser();
    parser.setGroup(group);
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    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option indexOpt = obuilder.withLongName("dir").withRequired(true).withArgument(
        abuilder.withName("dir").withMinimum(1).withMaximum(1).create())
        .withDescription("The Lucene index directory").withShortName("d").create();

    Option outputOpt = obuilder.withLongName("output").withRequired(false).withArgument(
        abuilder.withName("output").withMinimum(1).withMaximum(1).create()).withDescription(
        "The output file. If not specified, the result is printed on console.").withShortName("o").create();

    Option fieldOpt = obuilder.withLongName("field").withRequired(true).withArgument(
        abuilder.withName("field").withMinimum(1).withMaximum(1).create())
        .withDescription("The content field in the index").withShortName("f").create();

    Option idFieldOpt = obuilder.withLongName("idField").withRequired(false).withArgument(
        abuilder.withName("idField").withMinimum(1).withMaximum(1).create()).withDescription(
        "The field for the document ID in the index.  If null, then the Lucene internal doc "
            + "id is used which is prone to error if the underlying index changes").withShortName("i").create();

    Option seqOpt = obuilder.withLongName("seqFileDir").withRequired(true).withArgument(
        abuilder.withName("seqFileDir").withMinimum(1).withMaximum(1).create()).withDescription(
        "The directory containing Sequence Files for the Clusters").withShortName("s").create();

    Option pointsOpt = obuilder.withLongName("pointsDir").withRequired(true).withArgument(
        abuilder.withName("pointsDir").withMinimum(1).withMaximum(1).create()).withDescription(
        "The directory containing points sequence files mapping input vectors to their cluster.  ")
        .withShortName("p").create();
    Option minClusterSizeOpt = obuilder.withLongName("minClusterSize").withRequired(false).withArgument(
        abuilder.withName("minClusterSize").withMinimum(1).withMaximum(1).create()).withDescription(
        "The minimum number of points required in a cluster to print the labels for").withShortName("m").create();
    Option maxLabelsOpt = obuilder.withLongName("maxLabels").withRequired(false).withArgument(
        abuilder.withName("maxLabels").withMinimum(1).withMaximum(1).create()).withDescription(
        "The maximum number of labels to print per cluster").withShortName("x").create();
    Option helpOpt = DefaultOptionCreator.helpOption();

    Group group = gbuilder.withName("Options").withOption(indexOpt).withOption(idFieldOpt).withOption(outputOpt)
        .withOption(fieldOpt).withOption(seqOpt).withOption(pointsOpt).withOption(helpOpt)
        .withOption(maxLabelsOpt).withOption(minClusterSizeOpt).create();
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    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = obuilder.withLongName("dir").withRequired(true).withArgument(
        abuilder.withName("dir").withMinimum(1).withMaximum(1).create())
        .withDescription("The Lucene directory").withShortName("d").create();

    Option outputOpt = obuilder.withLongName("output").withRequired(true).withArgument(
        abuilder.withName("output").withMinimum(1).withMaximum(1).create()).withDescription("The output file")
        .withShortName("o").create();

    Option fieldOpt = obuilder.withLongName("field").withRequired(true).withArgument(
        abuilder.withName("field").withMinimum(1).withMaximum(1).create()).withDescription(
        "The field in the index").withShortName("f").create();

    Option idFieldOpt = obuilder.withLongName("idField").withRequired(false).withArgument(
        abuilder.withName("idField").withMinimum(1).withMaximum(1).create()).withDescription(
        "The field in the index containing the index.  If null, then the Lucene internal doc "
            + "id is used which is prone to error if the underlying index changes").create();

    Option dictOutOpt = obuilder.withLongName("dictOut").withRequired(true).withArgument(
        abuilder.withName("dictOut").withMinimum(1).withMaximum(1).create()).withDescription(
        "The output of the dictionary").withShortName("t").create();

    Option weightOpt = obuilder.withLongName("weight").withRequired(false).withArgument(
        abuilder.withName("weight").withMinimum(1).withMaximum(1).create()).withDescription(
        "The kind of weight to use. Currently TF or TFIDF").withShortName("w").create();

    Option delimiterOpt = obuilder.withLongName("delimiter").withRequired(false).withArgument(
        abuilder.withName("delimiter").withMinimum(1).withMaximum(1).create()).withDescription(
        "The delimiter for outputting the dictionary").withShortName("l").create();

    Option powerOpt = obuilder.withLongName("norm").withRequired(false).withArgument(
        abuilder.withName("norm").withMinimum(1).withMaximum(1).create()).withDescription(
        "The norm to use, expressed as either a double or \"INF\" if you want to use the Infinite norm.  "
            + "Must be greater or equal to 0.  The default is not to normalize").withShortName("n").create();

    Option maxOpt = obuilder.withLongName("max").withRequired(false).withArgument(
        abuilder.withName("max").withMinimum(1).withMaximum(1).create()).withDescription(
        "The maximum number of vectors to output.  If not specified, then it will loop over all docs")
        .withShortName("m").create();

    Option minDFOpt = obuilder.withLongName("minDF").withRequired(false).withArgument(
        abuilder.withName("minDF").withMinimum(1).withMaximum(1).create()).withDescription(
        "The minimum document frequency.  Default is 1").withShortName("md").create();

    Option maxDFPercentOpt = obuilder.withLongName("maxDFPercent").withRequired(false).withArgument(
        abuilder.withName("maxDFPercent").withMinimum(1).withMaximum(1).create()).withDescription(
        "The max percentage of docs for the DF.  Can be used to remove really high frequency terms."
            + "  Expressed as an integer between 0 and 100. Default is 99.").withShortName("x").create();

    Option maxPercentErrorDocsOpt = obuilder.withLongName("maxPercentErrorDocs").withRequired(false).withArgument(
        abuilder.withName("maxPercentErrorDocs").withMinimum(1).withMaximum(1).create()).withDescription(
        "The max percentage of docs that can have a null term vector. These are noise document and can occur if the " +
            "analyzer used strips out all terms in the target field. This percentage is expressed as a value between 0 and 1. " +
            "The default is 0.").withShortName("err").create();

    Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h")
        .create();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(idFieldOpt).withOption(
        outputOpt).withOption(delimiterOpt).withOption(helpOpt).withOption(fieldOpt).withOption(maxOpt)
        .withOption(dictOutOpt).withOption(powerOpt).withOption(maxDFPercentOpt)
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  public static void main(String[] args) throws IOException, InvalidDatastoreException {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();
   
    Option pathOpt = obuilder.withLongName("model").withRequired(true).withArgument(
      abuilder.withName("model").withMinimum(1).withMaximum(1).create()).withDescription(
      "The path on HDFS as defined by the -source parameter").withShortName("m")
        .create();
   
    Option dirOpt = obuilder.withLongName("testDir").withRequired(true).withArgument(
      abuilder.withName("testDir").withMinimum(1).withMaximum(1).create()).withDescription(
      "The directory where test documents resides in").withShortName("d").create();
   
    Option helpOpt = DefaultOptionCreator.helpOption();
   
    Option encodingOpt = obuilder.withLongName("encoding").withArgument(
      abuilder.withName("encoding").withMinimum(1).withMaximum(1).create()).withDescription(
      "The file encoding.  Defaults to UTF-8").withShortName("e").create();
   
    Option defaultCatOpt = obuilder.withLongName("defaultCat").withArgument(
      abuilder.withName("defaultCat").withMinimum(1).withMaximum(1).create()).withDescription(
      "The default category Default Value: unknown").withShortName("default").create();
   
    Option gramSizeOpt = obuilder.withLongName("gramSize").withRequired(false).withArgument(
      abuilder.withName("gramSize").withMinimum(1).withMaximum(1).create()).withDescription(
      "Size of the n-gram. Default Value: 1").withShortName("ng").create();
   
    Option alphaOpt = obuilder.withLongName("alpha").withRequired(false).withArgument(
      abuilder.withName("a").withMinimum(1).withMaximum(1).create()).withDescription(
      "Smoothing parameter Default Value: 1.0").withShortName("a").create();
   
    Option verboseOutputOpt = obuilder.withLongName("verbose").withRequired(false).withDescription(
      "Output which values were correctly and incorrectly classified").withShortName("v").create();
   
    Option typeOpt = obuilder.withLongName("classifierType").withRequired(false).withArgument(
      abuilder.withName("classifierType").withMinimum(1).withMaximum(1).create()).withDescription(
      "Type of classifier: bayes|cbayes. Default Value: bayes").withShortName("type").create();
   
    Option dataSourceOpt = obuilder.withLongName("dataSource").withRequired(false).withArgument(
      abuilder.withName("dataSource").withMinimum(1).withMaximum(1).create()).withDescription(
      "Location of model: hdfs").withShortName("source").create();
   
    Option methodOpt = obuilder.withLongName("method").withRequired(false).withArgument(
      abuilder.withName("method").withMinimum(1).withMaximum(1).create()).withDescription(
      "Method of Classification: sequential|mapreduce. Default Value: mapreduce").withShortName("method")
        .create();
   
    Option confusionMatrixOpt = obuilder.withLongName("confusionMatrix").withRequired(false).withArgument(
        abuilder.withName("confusionMatrix").withMinimum(1).withMaximum(1).create()).withDescription(
        "Export ConfusionMatrix as SequenceFile").withShortName("cm").create();
     
    Group group = gbuilder.withName("Options").withOption(defaultCatOpt).withOption(dirOpt).withOption(
      encodingOpt).withOption(gramSizeOpt).withOption(pathOpt).withOption(typeOpt).withOption(dataSourceOpt)
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  public static void main(String[] args) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();
   
    Option helpOpt = DefaultOptionCreator.helpOption();
   
    Option inputDirOpt = DefaultOptionCreator.inputOption().create();
   
    Option outputOpt = DefaultOptionCreator.outputOption().create();
   
    Option gramSizeOpt = obuilder.withLongName("gramSize").withRequired(false).withArgument(
      abuilder.withName("gramSize").withMinimum(1).withMaximum(1).create()).withDescription(
      "Size of the n-gram. Default Value: 1 ").withShortName("ng").create();
   
    Option minDfOpt = obuilder.withLongName("minDf").withRequired(false).withArgument(
        abuilder.withName("minDf").withMinimum(1).withMaximum(1).create()).withDescription(
        "Minimum Term Document Frequency: 1 ").withShortName("mf").create();
   
    Option minSupportOpt = obuilder.withLongName("minSupport").withRequired(false).withArgument(
        abuilder.withName("minSupport").withMinimum(1).withMaximum(1).create()).withDescription(
        "Minimum Support (Term Frequency): 1 ").withShortName("ms").create();
   
    Option alphaOpt = obuilder.withLongName("alpha").withRequired(false).withArgument(
      abuilder.withName("a").withMinimum(1).withMaximum(1).create()).withDescription(
      "Smoothing parameter Default Value: 1.0").withShortName("a").create();
   
    Option typeOpt = obuilder.withLongName("classifierType").withRequired(false).withArgument(
      abuilder.withName("classifierType").withMinimum(1).withMaximum(1).create()).withDescription(
      "Type of classifier: bayes|cbayes. Default: bayes").withShortName("type").create();
   
    Option dataSourceOpt = obuilder.withLongName("dataSource").withRequired(false).withArgument(
      abuilder.withName("dataSource").withMinimum(1).withMaximum(1).create()).withDescription(
      "Location of model: hdfs. Default Value: hdfs").withShortName("source").create();
   
    Option skipCleanupOpt = obuilder.withLongName("skipCleanup").withRequired(false).withDescription(
        "Skip cleanup of feature extraction output").withShortName("sc").create();
   
    Group group = gbuilder.withName("Options").withOption(gramSizeOpt).withOption(helpOpt).withOption(
      inputDirOpt).withOption(outputOpt).withOption(typeOpt).withOption(dataSourceOpt).withOption(alphaOpt)
        .withOption(minDfOpt).withOption(minSupportOpt).withOption(skipCleanupOpt).create();
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    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();
   
    Option pathOpt = obuilder.withLongName("path").withRequired(true).withArgument(
      abuilder.withName("path").withMinimum(1).withMaximum(1).create()).withDescription(
      "The local file system path").withShortName("m").create();
   
    Option classifyOpt = obuilder.withLongName("classify").withRequired(true).withArgument(
      abuilder.withName("classify").withMinimum(1).withMaximum(1).create()).withDescription(
      "The doc to classify").withShortName("").create();
   
    Option encodingOpt = obuilder.withLongName("encoding").withRequired(true).withArgument(
      abuilder.withName("encoding").withMinimum(1).withMaximum(1).create()).withDescription(
      "The file encoding.  Default: UTF-8").withShortName("e").create();
   
    Option analyzerOpt = obuilder.withLongName("analyzer").withRequired(true).withArgument(
      abuilder.withName("analyzer").withMinimum(1).withMaximum(1).create()).withDescription(
      "The Analyzer to use").withShortName("a").create();
   
    Option defaultCatOpt = obuilder.withLongName("defaultCat").withRequired(true).withArgument(
      abuilder.withName("defaultCat").withMinimum(1).withMaximum(1).create()).withDescription(
      "The default category").withShortName("d").create();
   
    Option gramSizeOpt = obuilder.withLongName("gramSize").withRequired(true).withArgument(
      abuilder.withName("gramSize").withMinimum(1).withMaximum(1).create()).withDescription(
      "Size of the n-gram").withShortName("ng").create();
   
    Option typeOpt = obuilder.withLongName("classifierType").withRequired(true).withArgument(
      abuilder.withName("classifierType").withMinimum(1).withMaximum(1).create()).withDescription(
      "Type of classifier").withShortName("type").create();
   
    Option dataSourceOpt = obuilder.withLongName("dataSource").withRequired(true).withArgument(
      abuilder.withName("dataSource").withMinimum(1).withMaximum(1).create()).withDescription(
      "Location of model: hdfs").withShortName("source").create();
   
    Group options = gbuilder.withName("Options").withOption(pathOpt).withOption(classifyOpt).withOption(
      encodingOpt).withOption(analyzerOpt).withOption(defaultCatOpt).withOption(gramSizeOpt).withOption(
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