Exemplo n.º 1
0
 long ans() {
   if (_ans != -3) return _ans;
   if (children.size() == 0) {
     if (this == EMPTY_LEAF) return 0;
     return i;
   }
   long digits = 0;
   long ret = 0;
   for (int i = children.size() - 1; i >= 0; i--) {
     Node node = children.get(i);
     ret = (ret + (node.ans() * modPow(digits)) % MOD) % MOD;
     digits += node.size();
     digits %= MOD - 1;
   }
   _ans = ret;
   return ret;
 }
Exemplo n.º 2
0
  /** @param args */
  public static void main(final String[] args) throws Exception {
    final BufferedReader br =
        new BufferedReader(
            new InputStreamReader(
                (new GZIPInputStream(
                    new FileInputStream(
                        new File(
                            new File(System.getProperty("user.dir")), "testdata/mobo1.txt.gz"))))));

    final List<Instance> instances = Lists.newLinkedList();

    int count = 0;
    while (true) {
      count++;
      final String line = br.readLine();
      if (line == null) {
        break;
      }
      final JSONObject jo = (JSONObject) JSONValue.parse(line);
      final HashMapAttributes a = new HashMapAttributes();
      a.putAll((JSONObject) jo.get("attributes"));
      Instance instance = new Instance(a, (String) jo.get("output"));
      instances.add(instance);
    }

    final List<Instance> train = instances.subList(0, instances.size() / 2);
    final List<Instance> test = instances.subList(instances.size() / 2 + 1, instances.size() - 1);

    System.out.println("Read " + instances.size() + " instances");

    System.out.println("Testing scorers with single decision node");
    for (final Scorer scorer : Sets.newHashSet(new Scorer1())) {
      final TreeBuilder tb = new TreeBuilder(scorer);

      final long startTime = System.currentTimeMillis();
      final Node tree = tb.buildPredictiveModel(train).node;
      System.out.println(
          scorer.getClass().getSimpleName()
              + " build time "
              + (System.currentTimeMillis() - startTime)
              + ", size: "
              + tree.size()
              + " mean depth: "
              + tree.meanDepth());

      int correctlyClassified = 0;
      for (Instance testInstance : test) {
        String result = (String) tree.getLeaf(testInstance.getAttributes()).getBestClassification();
        if (result.equals(testInstance.getClassification())) {
          correctlyClassified++;
        }
      }
      System.out.println(", accuracy: " + (double) correctlyClassified / test.size());

      System.out.println("Testing random forest");

      for (int i = 2; i <= 20; i++) {
        RandomForestBuilder rfBuilder = new RandomForestBuilder(new TreeBuilder());
        RandomForest randomForest = rfBuilder.buildPredictiveModel(train);
        correctlyClassified = 0;
        for (Instance testInstance : test) {
          Serializable result =
              randomForest.getClassificationByMaxProb(testInstance.getAttributes());
          if (result.equals(testInstance.getClassification())) {
            correctlyClassified++;
          }
        }
        System.out.println(
            "accuracy with " + i + " trees: " + (double) correctlyClassified / test.size());
        // ObjectOutputStream out = new ObjectOutputStream(new FileOutputStream(new
        // File("baggedTree.ser")));
        // out.writeObject(baggedTree);
      }
    }
  }