Package cc.mallet.topics

Examples of cc.mallet.topics.LDAStream

    // Process the command-line options
    CommandOption.setSummary (TopicTrain.class,
                  "A tool for training and test streamline topic model.");
    CommandOption.process (TopicTrain.class, args);

    LDAStream lda = null;

    if (inputFile.value != null) {
      InstanceList instances = InstanceList.load (new File(inputFile.value));
      System.out.println ("Training Data loaded.");
      lda=new LDAStream(numTopics.value, alpha.value, beta.value);
    if(testFile.value != null) {
      InstanceList testing = InstanceList.load(new File(testFile.value));
     lda.setTopicDisplay(showTopicsInterval.value, topWords.value);

    if (outputModelInterval.value != 0) {
      lda.setModelOutput(outputModelInterval.value, outputModelFilename.value);


        if (randomSeed.value != 0) {

        if (outputStateInterval.value != 0) {
            lda.setSaveState(outputStateInterval.value, stateFile.value);

    //save the model, we need typeTopicCounts and tokensPerTopic for empirical likelihood
    lda.write(new File (inputFile.value + ".model"));

    if (topicKeysFile.value != null) {
      lda.printTopWords(new File(topicKeysFile.value), topWords.value, false);
    if (topicKeysFile.value != null) {
      lda.printTopWords(new File(topicKeysFile.value), topWords.value, false);
    if (topicTypesFile.value != null) {
      lda.printPhi(new File(topicTypesFile.value), 1e-4);
    if (stateFile.value != null) {
      lda.printState (lda.getData(), new File(stateFile.value));
    if (docTopicsFile.value != null) {
      lda.printDocumentTopics(lda.getData(), new PrintWriter (new FileWriter ((new File(docTopicsFile.value)))),
                  docTopicsThreshold.value, docTopicsMax.value);


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