Examples of nblabels()


Examples of org.apache.mahout.classifier.df.data.Dataset.nblabels()

   
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      Configuration conf = context.getConfiguration();
      Dataset dataset = Builder.loadDataset(conf);
      setup(dataset.nblabels());
    }
   
    /**
     * Useful when testing
     */
 
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Examples of org.apache.mahout.classifier.df.data.Dataset.nblabels()

   
    Path datasetPath = new Path(datasetStr);
    Dataset dataset = Dataset.load(conf, datasetPath);
   
    // currents[label] = next partition file where to place the tuple
    int[] currents = new int[dataset.nblabels()];
   
    // currents is initialized randomly in the range [0, numpartitions[
    Random random = RandomUtils.getRandom();
    for (int c = 0; c < currents.length; c++) {
      currents[c] = random.nextInt(numPartitions);
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Examples of org.apache.mahout.classifier.df.data.Dataset.nblabels()

   
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      Configuration conf = context.getConfiguration();
      Dataset dataset = Builder.loadDataset(conf);
      setup(dataset.nblabels());
    }
   
    /**
     * Useful when testing
     */
 
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Examples of org.apache.mahout.classifier.df.data.Dataset.nblabels()

   
    Path datasetPath = new Path(datasetStr);
    Dataset dataset = Dataset.load(conf, datasetPath);
   
    // currents[label] = next partition file where to place the tuple
    int[] currents = new int[dataset.nblabels()];
   
    // currents is initialized randomly in the range [0, numpartitions[
    Random random = RandomUtils.getRandom();
    for (int c = 0; c < currents.length; c++) {
      currents[c] = random.nextInt(numPartitions);
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Examples of org.apache.mahout.df.data.Dataset.nblabels()

   
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      Configuration conf = context.getConfiguration();
      Dataset dataset = Builder.loadDataset(conf);
      setup(dataset.nblabels());
    }
   
    /**
     * Useful when testing
     */
 
View Full Code Here

Examples of org.apache.mahout.df.data.Dataset.nblabels()

   
    Path datasetPath = new Path(datasetStr);
    Dataset dataset = Dataset.load(conf, datasetPath);
   
    // currents[label] = next partition file where to place the tuple
    int[] currents = new int[dataset.nblabels()];
   
    // currents is initialized randomly in the range [0, numpartitions[
    Random random = RandomUtils.getRandom();
    for (int c = 0; c < currents.length; c++) {
      currents[c] = random.nextInt(numPartitions);
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Examples of org.apache.mahout.df.data.Dataset.nblabels()

    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
    treeBuilder.setM(m);
   
    Dataset dataset = Dataset.load(getConf(), datasetPath);
   
    ForestPredictions callback = isOob ? new ForestPredictions(dataset.nbInstances(), dataset.nblabels())
        : null;
   
    Builder forestBuilder;
   
    if (isPartial) {
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Examples of org.apache.mahout.df.data.Dataset.nblabels()

    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
    treeBuilder.setM(m);
   
    Dataset dataset = Dataset.load(getConf(), datasetPath);
   
    ForestPredictions callback = isOob ? new ForestPredictions(dataset.nbInstances(), dataset.nblabels())
        : null;
   
    Builder forestBuilder;
   
    if (isPartial) {
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Examples of org.apache.mahout.df.data.Dataset.nblabels()

    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
    treeBuilder.setM(m);
   
    Dataset dataset = Dataset.load(getConf(), datasetPath);
   
    ForestPredictions callback = isOob ? new ForestPredictions(dataset.nbInstances(), dataset.nblabels())
        : null;
   
    Builder forestBuilder;
   
    if (isPartial) {
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Examples of org.apache.mahout.df.data.Dataset.nblabels()

    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
    treeBuilder.setM(m);
   
    Dataset dataset = Dataset.load(getConf(), datasetPath);
   
    ForestPredictions callback = isOob ? new ForestPredictions(dataset.nbInstances(), dataset.nblabels())
        : null;
   
    Builder forestBuilder;
   
    if (isPartial) {
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