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Logo r-cran-randomSurvivalForest 3.6.3

by r-cran-robot - May 21, 2010, 00:00:00 CET [ Project Homepage BibTeX Download ] 3698 views, 760 downloads, 1 subscription

About: Random Survival Forests

Changes:

Fetched by r-cran-robot on 2013-03-01 00:00:08.083405


Logo r-cran-RSNNS 0.4-3

by r-cran-robot - January 10, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 4533 views, 756 downloads, 0 subscriptions

About: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)

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Fetched by r-cran-robot on 2012-02-01 00:00:11.194183


Logo sofia ml 0.1

by dsculley - December 29, 2009, 23:30:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4459 views, 754 downloads, 0 comments, 1 subscription

About: A fast implementation of several stochastic gradient descent learners for classification, ranking, and ROC area optimization, suitable for large, sparse data sets. Includes Pegasos SVM, SGD-SVM, Passive-Aggressive Perceptron, Perceptron with Margins, Logistic Regression, and ROMMA. Commandline utility and API libraries are provided.

Changes:

Initial Announcement on mloss.org.


Logo Nen Beta

by pascal - February 19, 2012, 00:31:34 CET [ Project Homepage BibTeX Download ] 2461 views, 752 downloads, 1 subscription

About: 3-layer neural network for regression with sigmoid activation function and command line interface similar to LibSVM.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-CORElearn 0.9.42

by r-cran-robot - October 17, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 3171 views, 748 downloads, 0 subscriptions

About: CORElearn - classification, regression, feature evaluation and ordinal evaluation

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Fetched by r-cran-robot on 2014-04-01 00:00:04.667607


Logo pboost 1.0

by nowozin - November 13, 2007, 08:48:28 CET [ Project Homepage BibTeX Download ] 3085 views, 739 downloads, 0 subscriptions

About: The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of [...]

Changes:

Initial Announcement on mloss.org.


Logo HDDM 0.5

by Wiecki - April 24, 2013, 02:53:07 CET [ Project Homepage BibTeX Download ] 2765 views, 733 downloads, 1 subscription

About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making.

Changes:
  • New and improved HDDM model with the following changes:
    • Priors: by default model will use informative priors (see http://ski.clps.brown.edu/hddm_docs/methods.html#hierarchical-drift-diffusion-models-used-in-hddm) If you want uninformative priors, set informative=False.
    • Sampling: This model uses slice sampling which leads to faster convergence while being slower to generate an individual sample. In our experiments, burnin of 20 is often good enough.
    • Inter-trial variablity parameters are only estimated at the group level, not for individual subjects.
    • The old model has been renamed to HDDMTransformed.
    • HDDMRegression and HDDMStimCoding are also using this model.
  • HDDMRegression takes patsy model specification strings. See http://ski.clps.brown.edu/hddm_docs/howto.html#estimate-a-regression-model and http://ski.clps.brown.edu/hddm_docs/tutorial_regression_stimcoding.html#chap-tutorial-hddm-regression
  • Improved online documentation at http://ski.clps.brown.edu/hddm_docs
  • A new HDDM demo at http://ski.clps.brown.edu/hddm_docs/demo.html
  • Ratcliff's quantile optimization method for single subjects and groups using the .optimize() method
  • Maximum likelihood optimization.
  • Many bugfixes and better test coverage.
  • hddm_fit.py command line utility is depracated.

Logo sccan 0.0

by stnava - January 13, 2011, 18:14:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2999 views, 733 downloads, 1 subscription

About: A work in progress

Changes:

Initial Announcement on mloss.org.


About: The package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive lasso, PLS, and Ridge Regression.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-relaxo 0.1-2

by r-cran-robot - June 1, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 2796 views, 725 downloads, 1 subscription

About: Relaxed Lasso

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.978325


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