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Logo Choquistic Utilitaristic Regression 1.00

by AliFall - April 17, 2015, 11:31:20 CET [ BibTeX BibTeX for corresponding Paper Download ] 1633 views, 681 downloads, 2 subscriptions

About: This Matlab package implements a method for learning a choquistic regression model (represented by a corresponding Moebius transform of the underlying fuzzy measure), using the maximum likelihood approach proposed in [2], eqquiped by sigmoid normalization, see [1].

Changes:

Initial Announcement on mloss.org.


Logo PyScriptClassifier 0.3.0

by cjb60 - November 25, 2015, 04:07:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2700 views, 679 downloads, 2 subscriptions

About: Easily prototype WEKA classifiers and filters using Python scripts.

Changes:

0.3.0

  • Filters have now been implemented.
  • Classifier and filter classes satisfy base unit tests.

0.2.1

  • Can now choose to save the script in the model using the -save flag.

0.2.0

  • Added Python 3 support.
  • Added uses decorator to prevent non-essential arguments from being passed.
  • Fixed nasty bug where imputation, binarisation, and standardisation would not actually be applied to test instances.
  • GUI in WEKA now displays the exception as well.
  • Fixed bug where single quotes in attribute values could mess up args creation.
  • ArffToPickle now recognises class index option and arguments.
  • Fix nasty bug where filters were not being saved and were made from scratch from test data.

0.1.1

  • ArffToArgs gets temporary folder in a platform-independent way, instead of assuming /tmp/.
  • Can now save args in ArffToPickle using save.

0.1.0

  • Initial release.

Logo AIDE 0.2

by khalili - January 3, 2014, 18:01:06 CET [ Project Homepage BibTeX Download ] 2438 views, 677 downloads, 1 subscription

About: AIDE (Automata Identification Engine) is a free open source tool for automata inference algorithms developed in C# .Net.

Changes:

Initial Announcement on mloss.org.


Logo Ordinal Choquistic Regression 1.00

by AliFall - January 30, 2014, 15:42:34 CET [ BibTeX BibTeX for corresponding Paper Download ] 2292 views, 675 downloads, 1 subscription

About: "Ordinal Choquistic Regression" model using the maximum likelihood

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 ] 4711 views, 673 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 ARTOS Adaptive Realtime Object Detection System 1.0

by erik - July 11, 2014, 22:02:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3189 views, 668 downloads, 2 subscriptions

About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories.

Changes:

Initial Announcement on mloss.org.


Logo Bayesian Model Averaging Library 0.3

by duric1 - November 16, 2013, 04:42:05 CET [ Project Homepage BibTeX Download ] 2215 views, 668 downloads, 1 subscription

About: Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Built-in priorss include coefficient priors (fixed, flexible and hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches.

Changes:

Initial Announcement on mloss.org.


  • Authors: Duric
  • License: Gnu
  • Programming Language: R

About: Robust sparse representation has shown significant potential in solving challenging problems in computer vision such as biometrics and visual surveillance. Although several robust sparse models have been proposed and promising results have been obtained, they are either for error correction or for error detection, and learning a general framework that systematically unifies these two aspects and explore their relation is still an open problem. In this paper, we develop a half-quadratic (HQ) framework to solve the robust sparse representation problem. By defining different kinds of half-quadratic functions, the proposed HQ framework is applicable to performing both error correction and error detection. More specifically, by using the additive form of HQ, we propose an L1-regularized error correction method by iteratively recovering corrupted data from errors incurred by noises and outliers; by using the multiplicative form of HQ, we propose an L1-regularized error detection method by learning from uncorrupted data iteratively. We also show that the L1-regularization solved by soft-thresholding function has a dual relationship to Huber M-estimator, which theoretically guarantees the performance of robust sparse representation in terms of M-estimation. Experiments on robust face recognition under severe occlusion and corruption validate our framework and findings.

Changes:

Initial Announcement on mloss.org.


Logo jackstraw 1.0

by nc - February 1, 2014, 22:53:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3108 views, 666 downloads, 1 subscription

About: Estimates statistical significance of association between variables and their principal components (PCs).

Changes:

Initial Announcement on mloss.org.


Logo Efficient Nonnegative Sparse Coding Algorithm 1.0

by openpr_nlpr - January 4, 2012, 09:44:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3282 views, 663 downloads, 1 subscription

About: Nonnegative Sparse Coding, Discriminative Semi-supervised Learning, sparse probability graph

Changes:

Initial Announcement on mloss.org.


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