1. Han J, Kamber M. Data Mining: Concepts and Techniques, Morgan Kaufmann 2000.
2. Catlett J. Megainduction: Machine learning on very large databases [Dissertation]. Dept. of Computer Science, University of Sydney, Australia, 1991.
3. Musick R, Catlett J, Russell S. Decision theoretic subsampling for induction on large databases. InProceedings of the Tenth International Conference on Machine Learning, Utgoff P E (ed.), San Francisco, CA: Morgan Kaufmann, 1992, pp. 212–219.
4. Chan P K, Stolfo S J. Learning arbiter and combiner trees from partitioned data for scaling machine learning. InProceedings of the First International Conference on Knowledge Discovery and Data Mining, Menlo Park, CA: AAAI Press, 1995, pp. 39–44.
5. Shafer J, Agrawal R, Mehta M. SPRINT: A scalable parallel classifier for data mining. InProceedings of the Twenty-Second VLDB Conference, San Francisco, CA: Morgan Kaufmann, 1996, pp. 544–555.