com.cra.bnet.learn
Interface DataSet

All Known Implementing Classes:
ComplexDataSet, SimpleDataSet

public interface DataSet

A data set used for learning Bayesian networks. A data set contains a number of cases. Each case represents a "snapshot" of the evidence in the network at a particular time. Each case consists of a number of observations. Each observation represents the evidence for a single node in the network.

A data set is usually visualized as a matrix where each row is one case, each column is one node in the network, and each element of the matrix is the observation of the corresponding node in the corresponding case.

Developers can implement the DataSet, Case, and Observation interfaces to provide data from any source for learning.


Method Summary
 int getCaseCount()
          Returns the number of cases in this data set.
 Iterator getCases()
          Returns an iterator over the cases in this data set.
 boolean getValuesParsed()
          Checks if any value was parsed in this object, in which case this parser is compatible with the selected data file.
 

Method Detail

getCaseCount

public int getCaseCount()
Returns the number of cases in this data set.

Returns:
the number of cases in this data set.

getCases

public Iterator getCases()
Returns an iterator over the cases in this data set. Objects returned by the iterator are guaranteed to be of type Case.

Returns:
an iterator over the cases in this data set.

getValuesParsed

public boolean getValuesParsed()
Checks if any value was parsed in this object, in which case this parser is compatible with the selected data file.

Returns:
true if compatible.