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;
}
/** @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);
}
}
}
