23-08-2012, 10:45 PM
i want a sample project with documentation for my reference using data mining with genetic algorithm concept? if you have please show me
23-08-2012, 10:45 PM
i want a sample project with documentation for my reference using data mining with genetic algorithm concept? if you have please show me
24-08-2012, 06:01 PM
Genetic Algorithms
• Population based search (parallel) – simultaneous search from multiple points in search space population members: potential solutions • Fitness function (search objective) – numerical “figure of merit”/utility measure of an individual selection • “Mating” and reproduction of individuals crossover, mutation • Evolution from one generation to the next iterative search, convergence Advantage GAs • General purpose, robust search technique – application to varied problem types • Data mining – fitness function: flexible expression of modeling criteria, tradeoffs amongst multiple objectives – models optimized to specific business objectives – diverse model representation – linear, non-linear interaction terms, rules, sequences, etc. GA Application Examples Function optimizers – difficult, discontinuous, multi-modal, noisy functions Combinatorial optimization – layout of VLSI circuits, factory scheduling, traveling salesman problem Design and Control – bridge structures, neural networks, communication networks design; control of chemical plants, pipelines Machine learning – classification rules, economic modeling, scheduling strategies Portfolio design, optimized trading models, direct marketing models, sequencing of TV advertisements, adaptive agents, data mining, etc. Data quality mining (DQM) is a new and ensuring information exploration strategy from the educational and the business perspective. Data excellent is important to organizations. People use information features as a device for evaluating data quality. The objective of DQM is to implement information exploration techniques to be able to identify, quantify, describe and appropriate information excellent inadequacies in very huge directories. Data excellent is essential for many programs of information development in databases (KDD). In this work, we have regarded four information features like precision, comprehensibility, interestingness and completeness. We have tried to develop Multi-objective Inherited Criteria (GA) centered strategy using linkage between feature choice and organization concept. The primary inspiration for using GA in the discovery of high-level forecast guidelines is that they execute a international search and cope better with function connections that the selfish concept introduction algorithms often used in information exploration.
24-08-2012, 06:08 PM
The entire data mining process is actually two logic control: one is the "dominant logic", a "hidden logic".
"Dominant logic" is to run through the logic of the machine learning algorithms, this logic is the crystallization of the wisdom of crowds on the philosophy behind these algorithms and implementation methods vary, but the only function for their logic are the same, namely through training training set that the parameters of the model (of course, also to pay attention to the format of the data, accuracy, note that the algorithm of time complexity and space complexity), in the process of learning machine learning algorithm among different algorithms have substantially the same function logic Accordingly, this logic in constant repetition being hard-coded into our brain, substantially without error in the use, and, thanks to their ancestors their contribution to our mistakes space is small. "Hidden logic" is when the practical application of machine learning algorithms for cognitive ability of the business, the business has too much personalization characteristics, therefore, it is hard to find a fixed logic can solve most of the problems possible problems you face every day is new, and sometimes you know what hinder your perception of the business, the tragedy is that sometimes you do not know what cognitive hinder your business and the most tragic, you are hindered, you have not been informed. sample of data mining available at http://jgap.sourceforge |
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