REFERENCES
1. Federal CIO Council Strategic Plan 2007–2009, http://www.cio.gov/documents/CIOCouncilStrategicPlan2007.
2. The Small Business Economy, an annual chapter in The Small Business Economy: A Report to the President, by Brian Headd, with accompanying appendix data tables by Brian Headd and Victoria Williams (http://www.sba.gov/advo/research/sbe.html).
3. P. C. Pendharkar and J. A. Rodger, “Maximum Entropy Density Estimation Using a Genetic Algorithm,” 2006 Proceedings INFORMS, 2006.
4. http://en.wikipedia.org/wiki/Machine_learning.
5. http://www.mccip.org.uk/arc/2006/glossary3.htm.
6. Department of Computer Science, University of California–Santa Cruz.
7. “A Tutorial on Clustering Algorithms,” http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/.
8. David E. Goldberg, Genetic Algorithms in Search of Optimization and Machine Learning, Addison-Wesley, Boston, 1989.
9. J. A. Rodger, “Book Review of Encyclopedia of Information Science and Technology,” Information Resources Management Journal, 18(3), 92–93, 2005.
10. P. C. Pendharkar and J. A. Rodger, “Response to Lin Zhao's Comments on Technical Efficiency-Based Selection of Learning Cases to Improve Forecasting of Neural Networks Under Monotonicity Assumption,” Journal of Forecasting, 739–740, 2004.
11. P. C. Pendharkar and J. A. Rodger, “Technical Efficiency-Based Selection of Learning Cases to Improve Forecasting Accuracy of Neural Networks Under Monotonicity Assumption,” Decision Support Systems, 117–136, 2003. ...
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