The nearest-neighbor algorithm described in Section 5.2 can be extended to handle nominal attributes. A variant of

Question:

The nearest-neighbor algorithm described in Section 5.2 can be extended to handle nominal attributes. A variant of the algorithm called PEBLS (Parallel Examplar-Based Learning System) by Cost and Salzberg [2] measures the distance between two values of a nominal attribute using the modified value difference metric (MVDM). Given a pair of nominal attribute values, V1 and V2, the distance between them is defined as follows:

where nij is the number of examples from class i with attribute value Vj and nj is the number of examples with attribute value Vj .
Consider the training set for the loan classification problem shown in Figure
5.9. Use the MVDM measure to compute the distance between every pair of attribute values for the Home Owner and Marital Status attributes.