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Showing Items 61-80 of 676 on page 4 of 34: Previous 1 2 3 4 5 6 7 8 9 Next Last

Logo KeBABS 1.5.4

by UBod - July 28, 2017, 09:55:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 49896 views, 9111 downloads, 0 subscriptions

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About: Kernel-Based Analysis of Biological Sequences

Changes:
  • importing apcluster package for avoiding method clashes
  • improved and completed change history in inst/NEWS and package vignette

Logo JMLR MOA Massive Online Analysis Nov-13

by abifet - April 4, 2014, 03:50:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 29697 views, 8988 downloads, 0 subscriptions

About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.

Changes:

New version November 2013


Logo r-cran-CORElearn 1.51.2

by r-cran-robot - August 8, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 40728 views, 8933 downloads, 0 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.164852


Logo Apache Mahout 0.11.1

by gsingers - November 9, 2015, 16:12:06 CET [ Project Homepage BibTeX Download ] 37268 views, 8836 downloads, 0 subscriptions

About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...]

Changes:

Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom. Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.


Logo MDP Modular toolkit for Data Processing 3.3

by otizonaizit - October 4, 2012, 15:17:33 CET [ Project Homepage BibTeX Download ] 38436 views, 8733 downloads, 0 subscriptions

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About: MDP is a Python library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. The base of available algorithms includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.

Changes:

What's new in version 3.3?

  • support sklearn versions up to 0.12
  • cleanly support reload
  • fail gracefully if pp server does not start
  • several bug-fixes and improvements

Logo MIToolbox 3.0.1

by apocock - March 2, 2017, 00:38:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 52462 views, 8684 downloads, 0 subscriptions

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Fixed a Windows compilation bug. MIToolbox v3 should now compile using Visual Studio.


Logo JMLR CAM Java 3.1

by wangny - October 14, 2013, 22:46:03 CET [ Project Homepage BibTeX Download ] 24707 views, 8637 downloads, 0 subscriptions

About: The CAM R-Java software provides a noval way to solve blind source separation problem.

Changes:

In this version, we fix the problem of not working under newest R version R-3.0.


Logo JMLR Matlab toolbox for submodular function optimization 2.0

by krausea - April 7, 2010, 09:53:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27452 views, 8123 downloads, 0 subscriptions

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others.

Changes:
  • Modified specification of optional parameters (using sfo_opt)
  • Added sfo_ls_lazy for maximizing nonnegative submodular functions
  • Added sfo_fn_infogain, sfo_fn_lincomb, sfo_fn_invert, ...
  • Added additional documentation and more examples
  • Now Octave ready

Logo JMLR Shark 2.3.0

by igel - October 24, 2009, 22:12:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 43658 views, 8094 downloads, 0 subscriptions

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About: SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides various machine learning and computational intelligence techniques.

Changes:
  • moved to GitHub
  • new build system
  • minor bug fixes

Logo r-cran-rgenoud 5.7-8.1

by r-cran-robot - June 3, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 34623 views, 7828 downloads, 0 subscriptions

About: R version of GENetic Optimization Using Derivatives

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:08.101900


Logo JMLR Surrogate Modeling Toolbox 7.0.2

by dgorissen - September 4, 2010, 07:48:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 26957 views, 7618 downloads, 0 subscriptions

About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive.

Changes:

Incremental update, fixing some cosmetic issues, coincides with JMLR publication.


Logo JMLR DLLearner 1.0

by Jens - February 13, 2015, 11:39:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37699 views, 7612 downloads, 0 subscriptions

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About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL.

Changes:

See http://dl-learner.org/development/changelog/.


Logo r-cran-klaR 0.6-8

by r-cran-robot - March 27, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 34892 views, 7565 downloads, 0 subscriptions

About: Classification and visualization

Changes:

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


Logo DiffSharp 0.7.7

by gbaydin - January 4, 2016, 00:57:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 38458 views, 7457 downloads, 0 subscriptions

About: DiffSharp is a functional automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products as higher-order functions. It allows exact and efficient calculation of derivatives, with support for nesting.

Changes:

Fixed: Bug fix in forward AD implementation of Sigmoid and ReLU for D, DV, and DM (fixes #16, thank you @mrakgr)

Improvement: Performance improvement by removing several more Parallel.For and Array.Parallel.map operations, working better with OpenBLAS multithreading

Added: Operations involving incompatible dimensions of DV and DM will now throw exceptions for warning the user


Logo revrand 1.0.0

by dsteinberg - January 29, 2017, 04:33:54 CET [ Project Homepage BibTeX Download ] 33810 views, 7299 downloads, 0 subscriptions

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About: A library of scalable Bayesian generalised linear models with fancy features

Changes:
  • 1.0 release!
  • Now there is a random search phase before optimization of all hyperparameters in the regression algorithms. This improves the performance of revrand since local optima are more easily avoided with this improved initialisation
  • Regression regularizers (weight variances) associated with each basis object, this approximates GP kernel addition more closely
  • Random state can be set for all random objects
  • Numerous small improvements to make revrand production ready
  • Final report
  • Documentation improvements

Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25671 views, 7280 downloads, 0 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo MLweb 1.2

by lauerfab - February 23, 2018, 15:40:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 31618 views, 7106 downloads, 0 subscriptions

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment.

Changes:
  • Add bibtex entry of corresponding Neurocomputing paper
  • Create javascript modules to avoid global scope pollution in web pages

Logo Malheur 0.5.4

by konrad - December 25, 2013, 13:20:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 36821 views, 7053 downloads, 0 subscriptions

About: Automatic Analysis of Malware Behavior using Machine Learning

Changes:

Support for new version of libarchive. Minor bug fixes.


Logo hca 0.63

by wbuntine - April 26, 2016, 15:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 52220 views, 7007 downloads, 0 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrected the new normalised Gamma model for topics so it works with multicore. Improvements to documentation. Added an asymptotic version of the generalised Stirling numbers so it longer fails when they run out of bounds on bigger data.


Logo Pyriel 1.5

by tfawcett - October 27, 2010, 09:12:53 CET [ BibTeX BibTeX for corresponding Paper Download ] 28522 views, 6945 downloads, 0 subscriptions

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining.

Changes:

1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "--score-for-class C" causes scores to be computed relative to a given (positive) class. For two-class problems. Fixed bug in example sampling code (--sample n) Fixed bug keeping old-style example formats (terminated by dot) from working. More code restructuring.


Showing Items 61-80 of 676 on page 4 of 34: Previous 1 2 3 4 5 6 7 8 9 Next Last