• EnKF

  • Referenced in 276 articles [sw02066]
  • sophisticated sequental data assimilation method. It applies an ensemble of model states to represent...
  • BayesTree

  • Referenced in 50 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 18 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 13 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 4 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...
  • EnsembleSVM

  • Referenced in 2 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...
  • 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...
  • 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...
  • Imbalanced-learn

  • Referenced in 3 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...
  • CIXL2

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

  • Referenced in 35 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...
  • pSuc-Lys

  • Referenced in 28 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...
  • subsemble

  • Referenced in 1 article [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...
  • clue

  • Referenced in 13 articles [sw09497]
  • computational environment for creating and analyzing cluster ensembles, with basic data structures for representing partitions ... facilities for computing on these, including methods for measuring proximity and obtaining consensus and ”secondary...
  • EnsemblePail

  • Referenced in 5 articles [sw27725]
  • from protein sequences. The computational method is based on ensembles of Support Vector Machine. EnsemblePail...
  • ESKNN

  • Referenced in 1 article [sw26841]
  • data is addressed by utilizing the ensemble method. A few optimal models are selected...
  • LeSiNN

  • Referenced in 1 article [sw20748]
  • anomalies directly. Although there is an existing method which is a special case of LeSiNN ... know. LeSiNN is the first ensemble method which works well with models trained using samples...