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Logo treelearn 1

by iskander - September 21, 2011, 16:12:27 CET [ Project Homepage BibTeX Download ] 3707 views, 987 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3703 views, 768 downloads, 1 subscription

About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.)

Changes:

Initial Announcement on mloss.org.


Logo ROCCH 2.2

by tfawcett - January 9, 2010, 07:47:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 3702 views, 1259 downloads, 0 comments, 1 subscription

About: Given many points in ROC (Receiver Operator Characteristics) space, computes the convex hull.

Changes:

Initial Announcement on mloss.org.


Logo GritBot 2.01

by zenog - September 2, 2011, 14:56:26 CET [ Project Homepage BibTeX Download ] 3673 views, 944 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo JMLR RL library 3.00.00

by frezza - January 13, 2015, 04:15:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3656 views, 1052 downloads, 2 subscriptions

About: A template based C++ reinforcement learning library

Changes:

Initial Announcement on mloss.org.


Logo AMIDST Toolbox 0.5.1

by ana - August 8, 2016, 13:45:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3645 views, 525 downloads, 4 subscriptions

About: A Java Toolbox for Scalable Probabilistic Machine Learning.

Changes:

The new added functionalities include support to Flink for distributed learning of probabilistic graphical models and support for Latent Dirichlet Allocation Models for text analysis purposes.

Detailed information can be found in the toolbox's web page


Logo fastICA 0.1

by maitra - February 28, 2013, 06:30:20 CET [ Project Homepage BibTeX Download ] 3567 views, 852 downloads, 1 subscription

About: The open-source C-package fastICA implements the fastICA algorithm of Aapo Hyvarinen et al. (URL: http://www.cs.helsinki.fi/u/ahyvarin/) to perform Independent Component Analysis (ICA) and Projection Pursuit. fastICA is released under the GNU Public License (GPL).

Changes:

Initial Announcement on mloss.org.


Logo r-cran-LogicForest 2.0.0

by r-cran-robot - September 20, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 3567 views, 784 downloads, 0 subscriptions

About: Logic Forest

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.077571


Logo Pattern Recognition for Neuroimaging Toolbox v1.1

by chrisp - September 16, 2013, 23:19:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3562 views, 708 downloads, 1 subscription

About: PRoNTo is freely available software and aims to facilitate the interaction between the neuroimaging and machine learning communities. The toolbox is based on pattern recognition techniques for the analysis of neuroimaging data. PRoNTo supports the analysis of all image modalities as long as they are NIfTI format files. However, only the following modalites have been tested for version 1.1: sMRI, fMRI, PET, FA (fractional anisotropy) and Beta (GLM coefficients) images.

Changes:

Initial Announcement on mloss.org.


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.


Showing Items 451-460 of 624 on page 46 of 63: First Previous 41 42 43 44 45 46 47 48 49 50 51 Next Last