Ensemble-Based Data Assimilation MethodsEnsemble-based methods have become very popular for data assimilation in numerical models of oceanic or atmospheric flows. Unlike the deterministic Extended Kalman Filter which explicitly describes thPierre Brasseur
Ensemble-based anomaly detection methods still face some challenges, however, such as data imbalance, time and space demand and the selection of base detectors. To this end, we propose a selective ensemble method for anomaly detection based on parallel learning (SEAD-PL). First, a differentiated...
the design of ensemble methods. This work shows that it provides a theoretical and practical tool to develop new ensemble methods well-tuned to the characteristics of a specific base learner. On the basis of the analysis and experiments performed on SVMs and bagged ensembles of ...
A novel localization scheme for scalar uncertainties in ensemble-based data assimilation methodsHistory matchingES-MDADistance-dependent localizationNon-distance-dependent localizationCorrelation-based adaptive localizationHistory matching, also known as data assimilation, is an inverse problem with multiple ...
Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling. In Proceedings of the Third International Workshop on New Frontiers in Mining Complex Patterns (NFMCP), Nancy, France, 19 September 2014; pp. 69-83. [CrossRef]Parinaz, S., Victor, H., & Matwin, S. (...
Tree-based ensemble methods and their applications in analytical chemistry[J] . Dong-Sheng Cao,Jian-Hua Huang,Yi-Zeng Liang.Trends in Analytical Chemistry . 2012D.-S. Cao, J.-H. Huang, Y.-Z. Liang, Q.-S. Xu, L.-X. Zhang, Tree-based ensemble methods and their applications in ...
Methods Background The most commonly known IOL power calculations formulae can be categorized into two main approaches: the first one is purely based on a linear regression analysis of retrospective cases, whereas the second one is based on a geometrical optics solution. The first IOL power calcul...
The methods for solving the class imbalance task can generally be divided into two categories: sampling approaches and algorithmic approaches. The sampling approach is factually a re-sizing procedure to balance the given imbalance dataset. The algorithmic approach can be viewed as a procedure to adju...
Each method is evaluated on two large, real datasets, and then the effective methods are combined to form a cascade MF ensemble scheme. The validation results on experiment datasets demonstrate that compared to a single MF-based recommender, our ensemble scheme could obtain a significant improvement...
Some research finds the efficacy of signature-based methods, which rely on predefined patterns to flag known botnet traffic. While this approach has demonstrated proficiency in recognizing established threats, it fundamentally lacks the flexibility to adapt to the polymorphic nature of contemporary botnets...