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Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 8305 views, 1738 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Logo ClusterEval 1.1

by cdevries - May 18, 2015, 22:01:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8276 views, 1775 downloads, 2 subscriptions

About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'.

Changes:

Moved project to GitHub.


Logo sofia ml 0.1

by dsculley - December 29, 2009, 23:30:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8270 views, 1480 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 HLearn 1.0

by mikeizbicki - May 9, 2013, 05:58:18 CET [ Project Homepage BibTeX Download ] 8258 views, 1999 downloads, 1 subscription

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure

Changes:

Updated to version 1.0


Logo Moses Decoder 2010-08-13

by oliver_wilson - September 3, 2010, 13:49:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8256 views, 2356 downloads, 0 comments, 1 subscription

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices.

Changes:

Initial Announcement on mloss.org.


Logo Alchemy 0.33

by marcs - December 16, 2008, 17:53:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8253 views, 2005 downloads, 1 subscription

About: Alchemy is a software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation. Alchemy allows you to [...]

Changes:

Initial Announcement on mloss.org.


Logo ILNumerics.Net 1.4.01

by haymo - October 14, 2008, 01:24:28 CET [ Project Homepage BibTeX Download ] 8237 views, 2013 downloads, 1 subscription

About: Intended for .NET developers wanting to implement algorithms directly in a common .NET language (recommended: C#). Support for n-dim generic arrays, LAPACK, FFT, cells, logicals, 2D&3D plotting [...]

Changes:

Initial Announcement on mloss.org.


About: GMRFLib is a library in C for fast and exact simulation of Gaussian Markov Random Fields (GMRF) on graphs.unconditional simulation of a GMRF, conditional simulation from a GMRF

Changes:

Initial Announcement on mloss.org.


Logo Spider 1.71

by jaseweston - November 19, 2007, 15:51:59 CET [ Project Homepage BibTeX Download ] 8175 views, 2454 downloads, 0 subscriptions

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About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...]

Changes:

Initial Announcement on mloss.org.


Logo ABACOC Adaptive Ball Cover for Classification 2.0

by kikot - May 29, 2015, 11:57:28 CET [ BibTeX BibTeX for corresponding Paper Download ] 8119 views, 2035 downloads, 3 subscriptions

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.

Changes:

version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at: https://github.com/ilaria-gori/ABACOC


Showing Items 301-310 of 674 on page 31 of 68: First Previous 26 27 28 29 30 31 32 33 34 35 36 Next Last