• SMOTE

  • Referenced in 125 articles [sw34239]
  • cost of the reverse error. Under-sampling of the majority (normal) class has been proposed ... that a combination of our method of over-sampling the minority (abnormal) class and under ... that a combination of our method of over-sampling the minority class and under-sampling ... priors in Naive Bayes. Our method of over-sampling the minority class involves creating synthetic...
  • DPpackage

  • Referenced in 62 articles [sw10495]
  • spaces are highly complex and hence sampling methods play a key role. This paper provides ... process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual...
  • IMFIL

  • Referenced in 39 articles [sw04814]
  • which derivative information is not available. Unlike methods that use interpolation to reconstruct the function ... area of derivative-free or sampling methods to be accompanied by publicly available software...
  • DAKOTA

  • Referenced in 64 articles [sw05202]
  • with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods...
  • gss

  • Referenced in 273 articles [sw06099]
  • penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian ... conditional density estimation under a variety of sampling schemes; and (iii) hazard rate estimation with ... unifying themes are the general penalized likelihood method and the construction of multivariate models with...
  • BUGS

  • Referenced in 358 articles [sw07885]
  • BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian ... models using Markov chain Monte Carlo (MCMC) methods. The project began...
  • emcee

  • Referenced in 29 articles [sw20217]
  • several advantages over traditional MCMC sampling methods and it has excellent performance as measured ... autocorrelation time (or function calls per independent sample). One major advantage of the algorithm ... Exploiting the parallelism of the ensemble method, emcee permits any user to take advantage...
  • APMC

  • Referenced in 27 articles [sw11483]
  • this paper, we propose an approximation method to verify quantitative properties on discrete Markov chains ... based on an execution sampling method. We also present an implementation and a few classical...
  • CMA-ES

  • Referenced in 102 articles [sw05063]
  • Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear ... evolution strategy, new candidate solutions are sampled according to a multivariate normal distribution ... covariance matrix adaptation (CMA) is a method to update the covariance matrix of this distribution ... classical optimization. In contrast to most classical methods, fewer assumptions on the nature...
  • HANSO

  • Referenced in 14 articles [sw05271]
  • based on the BFGS and gradient sampling methods. For general unconstrained minimization: convex or nonconvex ... BFGS, limited memory BFGS and gradient sampling methods, based on weak Wolfe line search...
  • GUI-HDMR

  • Referenced in 20 articles [sw07924]
  • controlled, then a quasi-random sampling method is preferable. This guarantees that the input space...
  • NewtonLib

  • Referenced in 265 articles [sw04796]
  • Software repository for Peter Deuflhards Book ”Newton Methods for Nonlinear Problems -- Affine Invariance and Adaptive ... intended usage. Please read our sample license agreement (or the german version) for more details...
  • FRAGSTATS

  • Referenced in 16 articles [sw31496]
  • image formats, and a variety of sampling methods for analyzing sub-landscapes...
  • CrossMine

  • Referenced in 15 articles [sw01967]
  • CrossMine employs tuple ID propagation, a novel method for virtually joining relations, which enables flexible ... essential statistics for classification. A selective sampling method is used to achieve high scalability w.r.t...
  • GSHMC

  • Referenced in 16 articles [sw02631]
  • method is a popular and rigorous method for sampling from a canonical ensemble ... step, the generalized hybrid Monte Carlo (GHMC) method can be implemented with a partial momentum ... some of the dynamic information throughout the sampling process similar to stochastic Langevin and Brownian ... Monte Carlo samples is observed. In this paper, we describe a method to achieve very...
  • CDVine

  • Referenced in 40 articles [sw08161]
  • joint maximum likelihood estimation. Sampling algorithms and plotting methods are also included. Data is assumed...
  • lda

  • Referenced in 14 articles [sw07319]
  • Collapsed Gibbs sampling methods for topic models. This package implements latent Dirichlet allocation...
  • TETRAD

  • Referenced in 386 articles [sw12177]
  • program is to provide sophisticated methods in a friendly interface requiring very little statistical sophistication ... about the true structure in the large sample limit, provided that structure and the sample...
  • mvBACON

  • Referenced in 26 articles [sw36501]
  • fact, they often contain outliers or subgroups. Methods for identifying multiple outliers and subgroups must ... point is. For samples of a sufficient size to support sophisticated methods, the computation cost ... outlier detection unattractive. All multiple outlier detection methods have suffered in the past from ... sample size. We propose a new general approach, based on the methods of Hadi (1992a...
  • PyMC

  • Referenced in 33 articles [sw10482]
  • problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness...