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About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data.

Changes:

o citation update

o plot function improved


Logo crfpp 0.53

by sonne - May 8, 2009, 08:46:44 CET [ Project Homepage BibTeX Download ] 3697 views, 2630 downloads, 1 subscription

About: CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data.

Changes:

Initial Announcement on mloss.org.


Logo Thresholding program 1.0

by openpr_nlpr - March 1, 2012, 03:18:52 CET [ Project Homepage BibTeX Download ] 3662 views, 442 downloads, 1 subscription

About: This is demo program on global thresholding for image of bright small objects, such as aircrafts in airports. the program include four method, otsu,2D-Tsallis,PSSIM, Smoothnees Method.

Changes:

Initial Announcement on mloss.org.


Logo Gesture Recogition Toolkit 0.1 Revision 289

by ngillian - December 13, 2013, 22:59:53 CET [ Project Homepage BibTeX Download ] 3578 views, 661 downloads, 1 subscription

About: The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library that has been specifically designed for real-time gesture recognition. It features a large number of machine-learning algorithms for both classification and regression in addition to a wide range of supporting algorithms for pre-processing, feature extraction and dataset management. The GRT has been designed for real-time gesture recognition, but it can also be applied to more general machine-learning tasks.

Changes:

Added Decision Tree and Random Forests.


Logo Hivemall 0.1

by myui - October 25, 2013, 08:43:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3560 views, 550 downloads, 1 subscription

About: Hivemall is a scalable machine learning library running on Hive/Hadoop, licensed under the LGPL 2.1.

Changes:
  • Enhancement

    • Added AROW regression
    • Added AROW with a hinge loss (arowh_regress())
  • Bugfix

    • Fixed a bug of null feature handling in classification/regression

Logo Ohmm 0.02

by hillbig - May 21, 2009, 10:07:53 CET [ Project Homepage BibTeX Download ] 3538 views, 971 downloads, 1 subscription

About: Ohmm is a library for learning hidden Markov models by using Online EM algorithm. This library is specialized for large scale data; e.g. 1 million words. The output includes parameters, and estimation results.

Changes:

Initial Announcement on mloss.org.


Logo Rudder 0.1

by dmcnelis - December 16, 2011, 22:00:45 CET [ Project Homepage BibTeX Download ] 3489 views, 1135 downloads, 1 subscription

About: An annotated java framework for machine learning, aimed at making it really easy to access analytically functions.

Changes:

Now supports OLS and GLS regression and NaiveBayes classification


Logo Pynopticon 0.1

by Wiecki - February 1, 2009, 18:55:10 CET [ Project Homepage BibTeX Download ] 3462 views, 972 downloads, 1 subscription

About: Pynopticon is a toolbox that allows you to create and train your own object recognition classifiers. It makes rapid prototyping of object recognition work flows a snap. Simply create a dataset of [...]

Changes:

Initial Announcement on mloss.org.


Logo HDDM 0.5

by Wiecki - April 24, 2013, 02:53:07 CET [ Project Homepage BibTeX Download ] 3445 views, 877 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 Kernel Machine Library 0.2

by pawelm - December 27, 2011, 17:14:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper ] 3442 views, 131 downloads, 1 subscription

About: The Kernel-Machine Library is a free (released under the LGPL) C++ library to promote the use of and progress of kernel machines.

Changes:

Updated mloss entry (minor fixes).


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