dynamic classifier hour

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  Long-term traffic pattern forecasting using dynamic classifier ...

  For each cluster, we train a dynamic classifier system for predicting the traffic variables (flow, speed and journey time). Our results on strategic road network data shows that the proposed method outperforms the existing ensemble and baseline models in …

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  Dynamic classifier selection: Recent advances and perspectives

  201851 · Dynamic classifier selection (DCS) is used in various domains to find the most suitable classifier from a group of different classifiers trained for the same classification problem [22]. Given ...

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  Windsifter Air Classifiers - Bradley Pulverizer Company

  2024620 · Stand-alone Air Classifier: Separate Coarse & Fine Particles Simultaneously Utilizing our proven technology, the Windsifter Air Classifier offers rugged and reliable air classification with efficient and economic operation. This dynamic air classifier provides capacities up to 250 tons per hour, with low power consumption and …

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  Characterization of defects using ultrasonic arrays: a dynamic ...

  In the field of nondestructive evaluation, accurate characterization of defects is required for the assessment of defect severity. Defect characterization is studied in this paper through the use of the ultrasonic scattering matrix, which can be extracted from the array measurements. Defects that have different shapes are classified into different defect …

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  Meta-learning-based sample discrimination framework for …

  Many real-world datasets encounter the issue of label noise (LN), which significantly degrades the learning performances of classification models. While ensemble learning (EL) has been widely employed to tackle this problem, the Dynamic Selection (DS) of classifiers, as a promising EL branch, is particularly sensitive to LN. To address this issue, a meta …

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  Methods for dynamic classifier selection - IEEE Xplore

  1999929 · In the field of pattern recognition, the concept of multiple classifier systems (MCS) was proposed as a method for the development of high-performance classification systems. At present, the common "operation" mechanism of MCS is the "combination" of classifier outputs. Recently, some researchers have pointed out the potentialities of …

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  (PDF) A Robust Dynamic Classifier Selection Approach for Hyperspectral ...

  2020915 · Building on the theory of imprecise probabilities, we develop a novel robust dynamic classifier selection (R-DCS) model for data classification with erroneous labels.

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  Dynamic Classifier (Loesche) - Corbis India

  Dynamic Classifier (Loesche) The classifier can separate particle sizes of 30µm – 250 µm (and generate products with residues of 3% R 30µm – 3% R 250 µm). The mechanical components of the classifier in combination with process influencing parameters can produce various particle size distributions.

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  Dynamic ensemble selection for multi-class classification …

  From this perspective, we propose a novel approach for combining one-class classifiers to solve multi class problems based on dynamic ensemble selection, which allows us to discard non-competent classifiers to improve the robustness of the combination phase.

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  Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains

  2020615 · Classifier chains is a key technique in multi-label classification, since it allows to consider label dependencies effectively. However, the classifiers are aligned according to a static order of the labels. In the concept of dynamic classifier chains (DCC) the label ordering is chosen for each prediction dynamically depending on the respective …

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