Data Mining With Neural Networks: Solving Business Problems by Joseph P. Bigus

By Joseph P. Bigus

Readers will locate concrete implementation suggestions, strengthened with real-world company examples and not less than formulation, and case reports drawn from a huge diversity of industries. The ebook illustrates the preferred info mining capabilities of class, clustering, modeling, and time-series forecasting--through examples built utilizing the IBM Neural community application.

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64-68. , and L. Osburn. 1993. Forecasting S&P and gold futures prices: An application of neural networks, Journal of Futures Markets, Vol. , pp. 631-ti43. L. L. Kennedy. 1994. Autonomously learning neural networks for clinical decision support, Proceedings of the International Conference on Neural Networks and Expert Systems in medicine and Healthcare, 1994, pp. 15-22. Komo, D. , C. Chang, and H. Ko. 1994. Stock market index prediction using neural networks, Proceedings of SPIE, Vol. 2243, pp. 516-26.

It is done every day by many people. However, it is by no means natural for most people. Even those with an aptitude for computer programming must be trained in the organized, step-by-step procedures required to write a program to get a computer to solve a problem. Some people are unable to think at the level of detail necessary to specify the sequence of elementary operations needed to perform even the most basic computing functions. Good programmers have linear, sequential thought processes. They view a problem as a connect-the-dots puzzle, where the first and last points are specified, and their job is to link the dots, one by one, until the solution emerges.

Perhaps the most common is the top-down structured approach, where a problem is broken down into subproblems. Data is identified and processes are defmed for manipulating the data. Well-known techniques are used to design programs and algorithms to solve the data processing problem. After that it is just a simple matter of programming. It's been done a million times. For the past 20 years, the computer science curriculum in universities has been based on this approach to solving problems with computers.

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