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Titlebook: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering; Larisa Angstenberger Book 2001 Springer Science+Business M

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https://doi.org/10.1007/978-3-540-47857-7 and the information about temporal changes in customer behaviour. This section contains a detailed description of the customer segments obtained during both types of analysis, an evaluation of the quality of the fuzzy partitions and a comparison of the different clustering results. The second appli
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Introduction,chnologies as well as statistical and mathematical techniques. Pattern recognition is the research area which provides the majority of methods for data mining and aims at supporting humans in analysing complex data structures automatically.
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Applications of Dynamic Pattern Recognition Methods, and the information about temporal changes in customer behaviour. This section contains a detailed description of the customer segments obtained during both types of analysis, an evaluation of the quality of the fuzzy partitions and a comparison of the different clustering results. The second appli
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Conclusions,ognise typical (static) states in the behaviour of a system/process given as points in the feature space at a certain time instant, and follow their temporal changes as time passes using updating techniques. Most of these algorithms are able to detect only gradual changes in the data structure by mo
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Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering
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