• EnKF

  • Referenced in 323 articles [sw02066]
  • sophisticated sequental data assimilation method. It applies an ensemble of model states to represent...
  • BayesTree

  • Referenced in 57 articles [sw07995]
  • BayesTree: Bayesian Methods for Tree Based Models: Implementation of BART: Bayesian Additive Regression Trees ... adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms in particular...
  • emcee

  • Referenced in 24 articles [sw20217]
  • tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC ... several advantages over traditional MCMC sampling methods and it has excellent performance as measured ... Exploiting the parallelism of the ensemble method, emcee permits any user to take advantage...
  • GSHMC

  • Referenced in 16 articles [sw02631]
  • sampling from a canonical ensemble. The HMC method is based on classical molecular dynamics simulations ... Carlo (GSHMC) method is applicable to NVT as well as NPT ensemble simulations...
  • LCE

  • Referenced in 5 articles [sw25277]
  • link-based cluster ensemble method for improved gene expression data analysis. MOTIVATION ... trivial to select the most effective clustering method and its parameterization, for a particular ... another, this is often sub-optimal. Cluster ensemble research solves this problem by automatically combining ... clustering. RESULTS: The link-based cluster ensemble (LCE) method, presented here, implements these ideas...
  • rotationForest

  • Referenced in 3 articles [sw24760]
  • Rotation forest: A new classifier ensemble method. IEEE Trans. Pattern Anal. Mach. Intell ... binary classification. Rotation forest is an ensemble method where each base classifier (tree...
  • Quantregforest

  • Referenced in 4 articles [sw14249]
  • Regression Forests is a tree-based ensemble method for estimation of conditional quantiles...
  • FastMMD

  • Referenced in 3 articles [sw31729]
  • FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test. The maximum mean discrepancy ... this study we propose an efficient method called FastMMD. The core idea of FastMMD ... provide a geometric explanation for our method, ensemble of circular discrepancy, which helps us understand ... lower variance than existing MMD approximation methods...
  • EnsembleSVM

  • Referenced in 3 articles [sw10892]
  • base models. It currently offers ensemble methods based on binary SVM models. Our implementation avoids ... constituent models. Experimental results show that using ensemble approaches can drastically reduce training complexity while...
  • subsemble

  • Referenced in 2 articles [sw18280]
  • package subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits. Subsemble is a general ... subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble...
  • Imbalanced-learn

  • Referenced in 4 articles [sw21535]
  • recognition. The implemented state-of-the-art methods can be categorized into 4 groups ... over- and under-sampling, and (iv) ensemble learning methods. The proposed toolbox depends only...
  • Euk-mPLoc

  • Referenced in 40 articles [sw26860]
  • blank, so far, all the existing methods for predicting eukaryotic protein subcellular localization are limited ... overcome such a barrier, a new ensemble classifier, named Euk-mPLoc, was developed that...
  • ebmc

  • Referenced in 1 article [sw32595]
  • package ebmc: Ensemble-Based Methods for Class Imbalance Problem. Four ensemble-based methods (SMOTEBoost, RUSBoost ... binary classification. Such methods adopt ensemble methods and data re-sampling techniques to improve model ... learning algorithms to build weak learners within ensemble models. References: Nitesh V. Chawla, Aleksandar Lazarevic...
  • PBoostGA

  • Referenced in 2 articles [sw17431]
  • success of boosting algorithms, a novel ensemble method PBoostGA is developed in this paper ... instance. According to the weight updating and ensemble member generating mechanism like AdaBoost.RT, a series...
  • BART-BMA

  • Referenced in 2 articles [sw23498]
  • Bayesian version of machine learning tree ensemble methods where the individual trees are the base...
  • pSuc-Lys

  • Referenced in 31 articles [sw16643]
  • random sampling, and (3) constructing an ensemble predictor by fusing a series of individual random ... indicated that it remarkably outperformed the existing methods. A user-friendly web-server for pSuc...
  • CellTrack

  • Referenced in 3 articles [sw16650]
  • cell boundaries, and constructed an ensemble of methods that achieves refined tracking results even under...
  • ArrayMining

  • Referenced in 2 articles [sw25183]
  • Application for Microarray Analysis Combining Ensemble and Consensus Methods with Cross-Study Normalization. BACKGROUND: Statistical ... multitude of available data sets and analysis methods, it is desirable to combine both different ... different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose ... choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration...
  • CIXL2

  • Referenced in 19 articles [sw03302]
  • ensemble of neural networks. The results obtained are above the performance of standard methods...
  • EnsemblePail

  • Referenced in 6 articles [sw27725]
  • from protein sequences. The computational method is based on ensembles of Support Vector Machine. EnsemblePail...