Information Fusion(Ensemble System)in Data Warehousing and Data Mining Год выпуска: 2013Автор: Amit GanatraИздательство: LAP Lambert Academic PublishingСтраниц: 200ISBN: 9783659395871Описание Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation...
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Антон В целом у препода к диплому нет замечаний. В дипломе все очень четко, по существу и актуально. Хорошая работа после вашего сопровождения, спасибо за ваши советы.
