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Logo KNIME 2.7.4

by toldo - April 29, 2013, 09:14:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3592 views, 636 downloads, 1 subscription

About: A comprehensive data mining environment, with a variety of machine learning components.

Changes:

Modifications following feedback from Knime main Author.


Logo PLEASD 0.1

by heroesneverdie - September 10, 2012, 03:53:26 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2742 views, 633 downloads, 1 subscription

About: PLEASD: A Matlab Toolbox for Structured Learning

Changes:

Initial Announcement on mloss.org.


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


About: TBEEF, a doubly ensemble framework for recommendation and prediction problems.

Changes:

Updated the included documentation.


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.


Logo KMLib sparse GPU SVM 0.1

by ksopyla - March 20, 2013, 14:30:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2472 views, 605 downloads, 1 subscription

About: Support Vectors Machine library in .net with CUDA support. Library includes GPU SVM solver for kernels linear,RBF,Chi-Square and Exp Chi-Square which use NVIDIA CUDA technology. It allows for classification of feature rich sparse datasets through utilization of sparse matrix formats CSR, Ellpack-R or Sliced EllR-T

Changes:

Initial Announcement on mloss.org.


Logo WebEnsemble 1.0

by jungc005 - May 8, 2012, 22:24:44 CET [ BibTeX Download ] 1694 views, 604 downloads, 1 subscription

About: Use the power of crowdsourcing to create ensembles.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-grpreg 2.3-0

by r-cran-robot - February 10, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 2373 views, 602 downloads, 0 subscriptions

About: Regularization paths for regression models with grouped covariates

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.489694


Logo Jubatus 0.5.0

by hido - November 30, 2013, 17:41:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3117 views, 601 downloads, 1 subscription

About: Jubatus is a general framework library for online and distributed machine learning. It currently supports classification, regression, clustering, recommendation, nearest neighbors, anomaly detection, and graph analysis. Loose model sharing provides higher scalability, better performance, and real-time capabilities, by combining online learning with distributed computations.

Changes:

0.5.0 add new supports for clustering and nearest neighbors. For more detail, see http://t.co/flMcTcYZVs


Logo r-cran-quantregForest 0.2-3

by r-cran-robot - June 1, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 2540 views, 597 downloads, 0 subscriptions

About: Quantile Regression Forests

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.576421


Showing Items 421-430 of 588 on page 43 of 59: First Previous 38 39 40 41 42 43 44 45 46 47 48 Next Last