Most developed learning algorithms are designed for environments in which all the relevant data is stored at single computer site. Advances in network technology and the Internet as well as the growing size of data have contributed to the proliferation of distributed data mining. Therefore, previously developed learning algorithms for computations with such distributed databases require that all data stored in distributed locations must be transferred to a common site and recompiled as one complete and local dataset before the construction can take place. The danger in this transfer is...