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Showing Items 411-420 of 567 on page 42 of 57: First Previous 37 38 39 40 41 42 43 44 45 46 47 Next Last

Logo Naive Bayes EM Algorithm 1.0.0

by openpr_nlpr - December 2, 2011, 05:35:09 CET [ Project Homepage BibTeX Download ] 2593 views, 607 downloads, 1 subscription

About: OpenPR-NBEM is an C++ implementation of Naive Bayes Classifier, which is a well-known generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. OpenPR-NBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectation-maximization estimate is used for semi-supervised and un-supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo Graphical Models and Conditional Random Fields Toolbox 2

by jdomke - January 5, 2012, 15:38:20 CET [ Project Homepage BibTeX Download ] 2572 views, 636 downloads, 1 subscription

About: This is a Matlab/C++ "toolbox" of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the high-treewidth setting.

Changes:

Initial Announcement on mloss.org.


Logo treelearn 1

by iskander - September 21, 2011, 16:12:27 CET [ Project Homepage BibTeX Download ] 2555 views, 626 downloads, 1 subscription

About: A python implementation of Breiman's Random Forests.

Changes:

Initial Announcement on mloss.org.


Logo KeBABS 1.0.5

by UBod - March 4, 2015, 22:34:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2551 views, 433 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • new accessors selGridRow, selGridCol and fullModel for class ModelSelectionResult
  • change of naming of feature weights because of change in LiblineaR 1.94-2
  • GCC warnings in Linux removed

Logo CPLVE 0.1

by wannesm - June 5, 2009, 13:06:42 CET [ BibTeX Download ] 2533 views, 817 downloads, 1 subscription

About: Preparing

Changes:

Initial Announcement on mloss.org.


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 2529 views, 579 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 MLPlot Beta

by pascal - August 22, 2011, 11:07:53 CET [ Project Homepage BibTeX Download ] 2526 views, 521 downloads, 1 subscription

About: MLPlot is a lightweight plotting library written in Java.

Changes:

Initial Announcement on mloss.org.


Logo QuickDT 0.1

by sanity - September 21, 2011, 13:43:37 CET [ Project Homepage BibTeX Download ] 2523 views, 747 downloads, 1 subscription

About: A decision tree learner that is designed to be reasonably fast, but the primary goal is ease of use

Changes:

Initial Announcement on mloss.org.


Logo GritBot 2.01

by zenog - September 2, 2011, 14:56:26 CET [ Project Homepage BibTeX Download ] 2509 views, 623 downloads, 1 subscription

About: GritBot is an data cleaning and outlier/anomaly detection program.

Changes:

Initial Announcement on mloss.org.


About: We study the problem of robust feature extraction based on L21 regularized correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that an L21-norm minimization can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1-norm and L21-norm minimization within a common framework. In algorithmic part, we propose an L21 regularized correntropy algorithm to extract informative features meanwhile to remove outliers from training data. A new alternate minimization algorithm is also developed to optimize the non-convex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearance-based model, called Sparse-Fisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets.

Changes:

Initial Announcement on mloss.org.


Showing Items 411-420 of 567 on page 42 of 57: First Previous 37 38 39 40 41 42 43 44 45 46 47 Next Last