Global ETD Search
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Showing 1 to 5 of 5 for “"Hybrid sampling"”.
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Supervised Classification of Imbalanced Bidding Fraud Data
… we assess and compare several advanced over-sampling (SMOTE), under-sampling (NearMiss and ClusterCentroid) and hybrid sampling (SMOTE-ENN and SMOTE-TomekLink) methods to solve the imbalanced learning problem. We utilize the Randomized Search Cross Validation to tune the hyper-parameters for …
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Accurate and Fast Approximate Graph Mining at Scale
… numerous graph-based applications. There exist sampling-based A-GPM systems to provide automation and generalization over a wide variety of use cases. Despite improved usability, there are two major obstacles that prevent existing A-GPM systems being adopted in practice. First, the termination …
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Data-Driven Approaches in Water Pipe Condition Assessment and Failure Prediction
… of rare failure events. This was supported by a hybrid sampling strategy and class weighting scheme, which together improved model accuracy and robustness, particularly under severely imbalanced data conditions. To further enhance predictive reliability, a stacked ensemble model was developed …
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Open quantum system theory from an information perspective
… neural network architecture by developing novel hybrid sampling strategies for a highly customizable compression of configuration space, rendering accurate and efficient simulations of asymmetric systems feasible. Finally, the applicability of the neural network is extended beyond pure spin-1/2 …
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Network reliability estimation
… reliability estimation. There are two main sampling techniques in reliability estimation: combinatorial and permutational sampling. Combinatorial sampling has the advantage of speed but has poor performance in rare event simulations. Permutational sampling gives good simulation performance …