How to use Isolationforest in weka? - weka

Question

I am trying to use isolationforest in weka ,but I cannot find a easy example which shows how to use it ,who can help me ?thanks in advance
import weka.classifiers.misc.IsolationForest;
public class Test2 {
public static void main(String[] args) {
IsolationForest isolationForest = new IsolationForest();
.....................................................
}
}

Answer 1

I strongly suggest you to study a little bit the implementation for IslationForest.
The following code work loading a CSV file with first column with Class (note: a single class value will produce only (1-anomaly score) if it's binary you will get the anomaly score too. Otherwise it just return an error). Note I skip the second column (that in my case is the uuid that is not needed for anomaly detection)
private static void findOutlier(File in, File out) throws Exception {
CSVLoader loader = new CSVLoader();
loader.setSource(new File(in.getAbsolutePath()));
Instances data = loader.getDataSet();
// setting class attribute if the data format does not provide this information
// For example, the XRFF format saves the class attribute information as well
if (data.classIndex() == -1)
data.setClassIndex(0);
String[] options = new String[2];
options[0] = "-R"; // "range"
options[1] = "2"; // first attribute
Remove remove = new Remove(); // new instance of filter
remove.setOptions(options); // set options
remove.setInputFormat(data); // inform filter about dataset **AFTER** setting options
Instances newData = Filter.useFilter(data, remove); // apply filter
IsolationForest randomForest = new IsolationForest();
randomForest.buildClassifier(newData);
// System.out.println(randomForest);
FileWriter fw = new FileWriter(out);
final Enumeration<Attribute> attributeEnumeration = data.enumerateAttributes();
for (Attribute e = attributeEnumeration.nextElement(); attributeEnumeration.hasMoreElements(); e = attributeEnumeration.nextElement()) {
fw.write(e.name());
fw.write(",");
}
fw.write("(1 - anomaly score),anomaly score\n");
for (int i = 0; i < data.size(); ++i) {
Instance inst = data.get(i);
final double[] distributionForInstance = randomForest.distributionForInstance(inst);
fw.write(inst + ", " + distributionForInstance[0] + "," + (1 - distributionForInstance[0]));
fw.write(",\n");
}
fw.flush();
}
The previous function will add at the CSV at last column the anomaly values. Please note I'm using a single class so for getting the corresponding anomaly I do 1 - distributionForInstance[0] otherwise you ca do simply distributionForInstance[1] .
A sample input.csv for getting (1-anomaly score):
Class,ignore, feature_0, feature_1, feature_2
A,1,21,31,31
A,2,41,61,81
A,3,61,37,34
A sample input.csv for getting (1-anomaly score) and anomaly score:
Class,ignore, feature_0, feature_1, feature_2
A,1,21,31,31
B,2,41,61,81
A,3,61,37,34