• EnKF

  • Referenced in 441 articles [sw02066]
  • used by Meteorological Centers. See the article ”Ensemble Kalman Filters Bring Weather Models ... start and spinup, and experienced users with optimized code which may increase the performence...
  • iPPBS-Opt

  • Referenced in 16 articles [sw22428]
  • Sequence-Based Ensemble Classifier for Identifying Protein-Protein Binding Sites by Optimizing Imbalanced Training Datasets ... Samples (IHTS) treatments to optimize the training dataset; (2) the ensemble voting approach to select...
  • Memtype-2L

  • Referenced in 39 articles [sw16472]
  • containing an ensemble classifier formed by fusing many powerful individual OET-KNN (Optimized Evidence-Theoretic...
  • ViennaRNA

  • Referenced in 23 articles [sw10504]
  • Zuker & Stiegler 1981) which yields a single optimal structure, the partition function algorithm of (McCaskill ... calculates base pair probabilities in the thermodynamic ensemble, and the suboptimal folding algorithm of (Wuchty ... within a given energy range of the optimal energy. For secondary structure comparison, the package...
  • LCE

  • Referenced in 5 articles [sw25277]
  • link-based cluster ensemble method for improved gene expression data analysis. MOTIVATION ... another, this is often sub-optimal. Cluster ensemble research solves this problem by automatically combining...
  • Signal-3L

  • Referenced in 16 articles [sw26857]
  • ensemble classifier formed by fusing many individual OET-KNN (optimized evidence-theoretic K nearest neighbor...
  • HyperLogLog

  • Referenced in 22 articles [sw02063]
  • extended abstract describes and analyses a near-optimal probabilistic algorithm, HyperLogLog, dedicated to estimating ... elements (the cardinality) of very large data ensembles. Using an auxiliary memory of m units ... only 1.5 kilobytes. The algorithm parallelizes optimally and adapts to the sliding window model...
  • OTE

  • Referenced in 1 article [sw33152]
  • package OTE: Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation. Functions ... creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin ... trees grown by random forest for the ensemble on the basis of their individual...
  • ESKNN

  • Referenced in 1 article [sw26841]
  • addressed by utilizing the ensemble method. A few optimal models are selected in the ensemble ... applied in selection of optimal models for the ensemble in the training function. The prediction...
  • DeepHyper

  • Referenced in 6 articles [sw41119]
  • pipeline optimization for ML (DeepHyper/POPT); neural architecture search (DeepHyper/NAS); hyperparameter search (DeepHyper/HPS); ensemble uncertainty quantification...
  • h2oEnsemble

  • Referenced in 1 article [sw33570]
  • version 3.0 and above). This type of ensemble learning is called ”super learning”, ”stacked regression ... stacking.” The Super Learner algorithm learns the optimal combination of the base learner fits ... shown that the super learner ensemble represents an asymptotically optimal system for learning...
  • PhaseMax

  • Referenced in 28 articles [sw24954]
  • formulate phase retrieval as a convex optimization problem, which we call PhaseMax. Unlike other convex ... broad range of random measurement ensembles, and we analyze the impact of measurement noise...
  • OTclust

  • Referenced in 1 article [sw35615]
  • Analysis. Providing mean partition for ensemble clustering by optimal transport alignment(OTA), uncertainty measures...
  • AutoGL

  • Referenced in 1 article [sw38082]
  • engineering, model training, hyper-parameter optimization, and auto ensemble. For each module, we provide numerous...
  • CIXL2

  • Referenced in 19 articles [sw03302]
  • used a set of functions to be optimized with regard to different criteria, such ... weight of each network in a ensemble of neural networks. The results obtained are above...
  • Gpos-PLoc

  • Referenced in 11 articles [sw26870]
  • discovery practice. In view of this, an ensemble classifier called ’Gpos-PLoc’ was developed ... which was engineered according to the optimized evidence-theoretic K-nearest neighbors rule...
  • Osprey

  • Referenced in 3 articles [sw21400]
  • ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal ... search, guaranteeing that the computational predictions are optimal with respect to the input model. Here ... resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application...
  • GBMCI

  • Referenced in 2 articles [sw11476]
  • boosting algorithm for survival analysis via direct optimization of concordance index. Survival analysis focuses ... hazard functions. Our nonparametric model utilizes an ensemble of regression trees to determine ... covariates. The ensemble model is trained using a gradient boosting method to optimize a smoothed...
  • PSPSO

  • Referenced in 1 article [sw39417]
  • package for parameters selection using particle swarm optimization. This paper reports a high-level python ... ensembles of machine learning algorithms parameters by using the particle swarm optimization (PSO) algorithm named...
  • PSOFuzzySVM-TMH

  • Referenced in 3 articles [sw27664]
  • identification of transmembrane helix segments using ensemble feature space by incorporated fuzzy support vector machine ... extraneous attributes are eradicated using an optimization selection technique, particle swarm optimization, from both feature ... spaces are combined in order to form ensemble feature space. Fuzzy-support vector Machine...