Htykuut

I am using Weka Java API. I trained a Bayesnet on an Instances object (data set) with class (label) unspecified.

/**

 * Initialization

 */

Instances data = ...;

BayesNet bn = new EditableBayesNet(data);

SearchAlgorithm learner = new TAN();

SimpleEstimator estimator = new SimpleEstimator();

/**

 * Training

 */

bn.initStructure();

learner.buildStructure(bayesNetworkModel, data);

Suppose the Instances object data has three attributes, A, B and C, and the dependency discovered is B->A, C->B.

The trained Bayesnet object bn is not for classification (I did not specify the class attribute for data), but I just want to calculate the joint probability of Pr(A=x, B=y). How do I get this probability from bn?

As far as I know, the distributionForInstance function of BayesNet may be the closest thing to use. It returns the probability distribution of a given instance (in our case, the instances is (A=x, B=y)). To use it, I could create a new Instance object testDataInstance and set value A=x and B=y, and call distributionForInstance with testDataInstance.

/**

 * Obtain Pr(A="x", B="y")

 */ 

Instance testDataInstance = new SparseInstance(3);

Instances testDataSet = new Instances(

            bn.m_Instances);

testDataSet.clear();

testDataInstance.setValue(testDataSet.attribute("A"), "x");

testDataInstance.setValue(testDataSet.attribute("B"), "y");

testDataSet.add(testDataInstance);

bn.distributionForInstance(testDataSet.firstInstance());

However, to my knowledge, the probability distribution indicates probabilities of all possible values for the class attribute in the bayesnet. As I did not specify a class attribute for data, it is unclear to me what the returned probability distribution means.