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Logo LibBi 1.0.0

by lawmurray - June 23, 2013, 09:04:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6730 views, 1552 downloads, 0 subscriptions

About: Bayesian state-space modelling and inference on high-performance computer hardware.

Changes:

Initial Announcement on mloss.org.


Logo SonS and MDSonS, Software for hierarchical clustering visualization V1

by marmarj3 - June 18, 2013, 12:18:05 CET [ Project Homepage BibTeX Download ] 5016 views, 1434 downloads, 0 subscriptions

About: This toolbox implements a novel visualization technique called Sectors on Sectors (SonS), and a extended version called Multidimensional Sectors on Sectors (MDSonS), for improving the interpretation of several data mining algorithms. The MDSonS method makes use of Multidimensional Scaling (MDS) to solve the main drawback of the previous method, namely, the lack of representing distances between pairs of clusters. These methods have been applied for visualizing the results of hierarchical clustering, Growing Hierarchical Self-Organizing Maps (GHSOM), classification trees and several manifolds. These methods make possible to extract all the existing relationships among centroids’ attributes at any hierarchy level.

Changes:

Initial Announcement on mloss.org.


Logo AISAIC 1.0.0610

by fydennis - June 13, 2013, 21:54:55 CET [ BibTeX Download ] 6560 views, 2387 downloads, 0 subscriptions

About: AISAIC software for analyzing human DNA copy numbers and detecting significant copy number alterations

Changes:

Initial Announcement on mloss.org.


Logo A Regularized Correntropy Framework for Robust Pattern Recognition 1.0

by openpr_nlpr - June 3, 2013, 09:59:51 CET [ Project Homepage BibTeX Download ] 7567 views, 1834 downloads, 0 subscriptions

About: This letter proposes a new multiple linear regression model using regularized correntropy for robust pattern recognition. First, we motivate the use of correntropy to improve the robustness of the classicalmean square error (MSE) criterion that is sensitive to outliers. Then an l1 regularization scheme is imposed on the correntropy to learn robust and sparse representations. Based on the half-quadratic optimization technique, we propose a novel algorithm to solve the nonlinear optimization problem. Second, we develop a new correntropy-based classifier based on the learned regularization scheme for robust object recognition. Extensive experiments over several applications confirm that the correntropy-based l1 regularization can improve recognition accuracy and receiver operator characteristic curves under noise corruption and occlusion.

Changes:

Initial Announcement on mloss.org.


Logo Half quadratic based Iterative Minimization for Robust Sparse Representation 1.0

by openpr_nlpr - June 3, 2013, 09:57:11 CET [ Project Homepage BibTeX Download ] 4949 views, 1266 downloads, 0 subscriptions

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 r-cran-ahaz 1.14

by r-cran-robot - June 3, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 20708 views, 4607 downloads, 0 subscriptions

About: Regularization for semiparametric additive hazards regression

Changes:

Fetched by r-cran-robot on 2018-09-01 00:00:03.378832


Logo Light Mutual Min Algorithm for Learning Bayesian Networks 1.0

by ramimahdi - May 14, 2013, 02:06:19 CET [ BibTeX BibTeX for corresponding Paper Download ] 6631 views, 2729 downloads, 0 subscriptions

About: A fast and robust learning of Bayesian networks

Changes:

Initial Announcement on mloss.org.


Logo HLearn 1.0

by mikeizbicki - May 9, 2013, 05:58:18 CET [ Project Homepage BibTeX Download ] 10937 views, 2786 downloads, 0 subscriptions

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 OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 20652 views, 4127 downloads, 0 subscriptions

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

Changes:
  • minor bugfix

Logo KNIME 2.7.4

by toldo - April 29, 2013, 09:14:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12449 views, 2249 downloads, 0 subscriptions

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

Changes:

Modifications following feedback from Knime main Author.


Logo Intelligent Parameter Utilization Tool 0.4

by feldob - April 28, 2013, 18:05:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6644 views, 1712 downloads, 0 subscriptions

About: A descriptive and programming language independent format and API for the simplified configuration, documentation, and design of computer experiments.

Changes:

Initial Announcement on mloss.org.


Logo HDDM 0.5

by Wiecki - April 24, 2013, 02:53:07 CET [ Project Homepage BibTeX Download ] 13457 views, 2960 downloads, 0 subscriptions

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 r-cran-rgp 0.2-4

by r-cran-robot - April 1, 2013, 00:00:08 CET [ Project Homepage BibTeX Download ] 18405 views, 3331 downloads, 0 subscriptions

About: R genetic programming framework

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:08.163887


Logo r-cran-pamr 1.54

by r-cran-robot - April 1, 2013, 00:00:06 CET [ Project Homepage BibTeX Download ] 47727 views, 9419 downloads, 0 subscriptions

About: Pam

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.709586


Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 26207 views, 5255 downloads, 0 subscriptions

About: Generalized linear and additive models by likelihood based boosting

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:04.893311


Logo r-cran-klaR 0.6-8

by r-cran-robot - March 27, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 34091 views, 7383 downloads, 0 subscriptions

About: Classification and visualization

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.722314


Logo MICP 1.04

by kay_brodersen - March 26, 2013, 12:42:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13935 views, 2702 downloads, 0 subscriptions

About: This toolbox implements models for Bayesian mixed-effects inference on classification performance in hierarchical classification analyses.

Changes:

In addition to the existing MATLAB implementation, the toolbox now also contains an R package of the variational Bayesian algorithm for mixed-effects inference.


Logo r-cran-partykit 0.1-5

by r-cran-robot - March 22, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 11889 views, 2619 downloads, 0 subscriptions

About: A Toolkit for Recursive Partytioning

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.838561


Logo KMLib sparse GPU SVM 0.1

by ksopyla - March 20, 2013, 14:30:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7485 views, 1985 downloads, 0 subscriptions

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 r-cran-nnet 7.3-6

by r-cran-robot - March 20, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 15702 views, 3514 downloads, 0 subscriptions

About: Feed-forward Neural Networks and Multinomial Log-Linear Models

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.544403


Showing Items 301-320 of 676 on page 16 of 34: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last