Oliver Ritthoff

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Real-world knowledge discovery processes typically consist of complex data pre-processing, machine learning, evaluation, and visualization steps. Hence a data mining platform should allow complex nested operator chains or trees, provide transparent data handling, comfortable parameter handling and optimization, be flexible, extendible and easy-to-use.(More)
Data preprocessing, especially in terms of feature selection and generation, is an important issue in data mining and knowledge discovery tasks. Genetic algorithms proved to work well on feature selection problems where the search space produced by the initial feature set already contains the target hypothesis. In cases where this precondition is not(More)
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