D.P. Greene, S.F. Smith, Using coverage as a model building constraint in learning classifier systems, Evolutionary Computation 2 (1) (1994) 67--91.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... function (Rendell, 1990) to weights and orientations for the k nearest neighbor algorithm (Kelly Davis, 1991; Punch et al. 1993) to finite state automata (Fogel et al. 1966) and context free grammars (Wyard, 1991) to production system like rules (Booker et al. 1989; De Jong et al. 1993; Greene Smith, 1993, 1994; Holland, 1986; Janikow, 1993) Financial Forecasting Using Genetic Algorithms 549 Higher level constructs such as neural networks and LISP programs are very powerful representations. However, this power comes at the expense of an additional layer of complexity. Neural networks require search ....

....Sikora and Shaw (1994) in their genetic classification system. Sequential niching repeatedly runs a traditional GA, each time making sure that the population searches a new area of the space. Two previous learning systems that utilize implicit niching methods also deserve mention. In both systems (Greene Smith, 1993, 1994; Schaffer, 1984, 1985) the Financial Forecasting Using Genetic Algorithms 551 fitness function is decomposed into independent components, and different population elements are assigned to optimize each component. Fitness Function: Credit Assignment Most research on classification by GA has ....

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Greene, D. P., and S. F. Smith. 1994. Using coverage as a model building constraint in learning classifier systems. Evolutionary Computation 2(1):6791.

....to various areas within KDD. Evolutionary techniques have primarily concentrated upon the KDD task of Feature Selection (e.g. Punch, 1993) and advances have been made in the modification of GA techniques to develop and maintain both single (GABL, GABIL, Spears, 1992) and multiple (COGIN, (Greene 1993, 1994) target concepts. Recent work within Feature Selection has moved onto the application of Genetic Programming with pruning techniques introduced to produce human readable results (e.g. Raymer, 1997) Applying evolutionary computing to Data Mining is a more complex task, directly tackling the ....

Greene, D.P., Smith, S.F. (1994), Using Coverage as a Model-Building Constraint in Learning Classifier Systems, Evolutionary Computation, 2(1).

.... considered to be a resource to be covered, in the sense of [59] then the LMS learning rule automatically shares this resource among overlapping RBFs, producing niches and cooperative coverage of the training examples in a manner analogous to that of recent genetic classifier systems [59] 64] [65]. IV. Genetic Encoding and Operators As discussed in Section III, each RBF in the population G k must be specified by a bit string OE i which encodes the center c i and width d i of the RBF. Before carrying out this encoding, the training data x j , j = 1; p in each generation are ....

D. P. Greene and S. F. Smith, "Using coverage as a model building constraint in learning classifier systems," Evolutionary Computation, vol. 2, no. 1, pp. 67--91, 1994.

....all the good schemata of the parents and produce offspring that are less fit than their parents. However, disruption is related to exploratory power, and it has been shown that crossover operators with greater exploratory power (and higher disruption) can perform better (e.g. Sys89] Esh91] GS94] The negative effects of disruption are eliminated by elitism. This hypothesis was made (but not confirmed) by Syswerda who thought that his experimental results which showed uniform crossover to perform better than both one point and twopoint crossover may have been partially caused by the use ....

D.P. Greene and S.F. Smith. Using coverage as a model building constraint in learning classifier systems. Evolutionary Computation, 2:67--91, 1994.

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D.P. Greene, S.F. Smith, Using coverage as a model building constraint in learning classifier systems, Evolutionary Computation 2 (1) (1994) 67--91.

No context found.

D. P. Greene and S. F. Smith, "Using coverage as a model building constraint in learning classifier systems," Evol. Comput., vol. 2, no. 1, pp. 67--91, 1994.

No context found.

D.P. Greene and S.F. Smith, "Using Coverage as a Model Building Constraint in Learning Classifier Systems," Evolutionary Computation, vol. 2, no. 1, pp. 67-91, 1994.

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