Applications of Data Mining in E-Business and Finance by Z.-H. Zhou

By Z.-H. Zhou

The applying of information Mining (DM) applied sciences has proven an explosive development in progressively more varied components of industrial, govt and technology. of crucial enterprise components are finance, specifically in banks and insurance firms, and e-business, reminiscent of internet portals, e-commerce and advert administration services.In spite of the shut dating among study and perform in info Mining, it's not effortless to discover info on one of the most very important concerns fascinated about actual global software of DM expertise, from enterprise and information realizing to assessment and deployment. Papers usually describe examine that was once built with no considering constraints imposed by means of the motivating software. while those matters are taken into consideration, they're often no longer mentioned intimately as the paper needs to specialize in the strategy. hence wisdom that may be important if you want to follow an analogous method on a comparable challenge isn't shared. The papers during this e-book handle a few of these matters. This ebook is of curiosity not just to info Mining researchers and practitioners, but additionally to scholars who desire to have an idea of the sensible matters serious about info Mining.

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1. The details of the other four trading strategies are not discussed here. Interested readers can refer to [18,19] for further information. The typical settings of various trading strategies are also obtained from [18]. Besides, the simple buy-and-hold strategy (BH) is also tested for comparison purpose. During the experiments, the trading strategies are always applied to a security/index with an initial capital of AU$10,000 for a security or AU$1,000,000 for an index. 2% of the traded value is charged for each trade (buy or sale).

Calculate the final total wealth for P , Pi1 , Pi2 , denoted by W , Wi1 , Wi2 (i = 1, 2, . . , n), respectively; 4. Calculate the maximum difference between Wi1 , Wi2 (i = 1, 2, . . , n) and W , denoted by Dmax : Dmax = max{|Wij − W ||i = 1, 2, . . , n; j = 1, 2} 5. Let the initial wealth be C; 6. Calculate fitness value Dmax W F = (1 − )+ C C This new fitness function depends on two factors: the absolute business performance and its resilience to parameter disturbance. The expectation is that such a fitness function will guide GA to find parameter settings with stable high business performance.

14] F. O. G. Ali and W. A. Wallace. Bridging the gap between business objectives and parameters of data mining algorithms. Decision Support Systems, 21(1):3–15, sep 1997. [15] A. A. Freitas. A critical review of multi-objective optimization in data mining: a position paper. ACM SIGKDD Explorations Newsletter, 6(2):77–86, dec 2004. [16] J. H. Holland. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, USA, 1975. [17] J. Ni and C. Zhang. A dynamic storage method for stock transaction data.

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