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Logo MPIKmeans 1.5

by pgehler - January 16, 2009, 15:48:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 43118 views, 6302 downloads, 0 subscriptions

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About: A K-means clustering implementation for command-line, Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle [...]

Changes:

Initial Announcement on mloss.org.


Logo JMLR scikitlearn 0.18.1

by fabianp - November 28, 2016, 17:45:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 42913 views, 15907 downloads, 0 subscriptions

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About: The scikit-learn project is a machine learning library in Python.

Changes:

Update for 0.18 .1


Logo ADAMS 17.12.0

by fracpete - December 20, 2017, 09:38:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 42527 views, 7630 downloads, 0 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes.

Changes:

Some highlights:

  • Code base was moved to Github
  • Nearly 90 new actors, 25 new conversions
  • much improved deeplearning4j module
  • experimental support for Microsoft's CNTK deep learning framework
  • rsync module
  • MEKA webservice module
  • improved support for image annotations
  • improved LaTeX support
  • Websocket support

Logo r-cran-Boruta 6.0.0

by r-cran-robot - September 1, 2018, 00:00:04 CET [ Project Homepage BibTeX Download ] 42111 views, 9112 downloads, 0 subscriptions

About: Wrapper Algorithm for All Relevant Feature Selection

Changes:

Fetched by r-cran-robot on 2018-09-01 00:00:04.516878


Logo r-cran-CoxBoost 1.4

by r-cran-robot - January 1, 2018, 00:00:07 CET [ Project Homepage BibTeX Download ] 42107 views, 8314 downloads, 0 subscriptions

About: Cox models by likelihood based boosting for a single survival endpoint or competing risks

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.280476


Logo MLDemos 0.5.1

by basilio - March 2, 2013, 16:06:13 CET [ Project Homepage BibTeX Download ] 41504 views, 8993 downloads, 0 subscriptions

About: MLDemos is a user-friendly visualization interface for various machine learning algorithms for classification, regression, clustering, projection, dynamical systems, reward maximisation and reinforcement learning.

Changes:

New Visualization and Dataset Features Added 3D visualization of samples and classification, regression and maximization results Added Visualization panel with individual plots, correlations, density, etc. Added Editing tools to drag/magnet data, change class, increase or decrease dimensions of the dataset Added categorical dimensions (indexed dimensions with non-numerical values) Added Dataset Editing panel to swap, delete and rename dimensions, classes or categorical values Several bug-fixes for display, import/export of data, classification performance

New Algorithms and methodologies Added Projections to pre-process data (which can then be classified/regressed/clustered), with LDA, PCA, KernelPCA, ICA, CCA Added Grid-Search panel for batch-testing ranges of values for up to two parameters at a time Added One-vs-All multi-class classification for non-multi-class algorithms Trained models can now be kept and tested on new data (training on one dataset, testing on another) Added a dataset generator panel for standard toy datasets (e.g. swissroll, checkerboard,...) Added a number of clustering, regression and classification algorithms (FLAME, DBSCAN, LOWESS, CCA, KMEANS++, GP Classification, Random Forests) Added Save/Load Model option for GMMs and SVMs Added Growing Hierarchical Self Organizing Maps (original code by Michael Dittenbach) Added Automatic Relevance Determination for SVM with RBF kernel (Thanks to Ashwini Shukla!)


Logo JMLR The Generalised Linear Models Inference and Estimation Toolbox 1.5

by hn - November 8, 2013, 13:58:03 CET [ Project Homepage BibTeX Download ] 41206 views, 10146 downloads, 0 subscriptions

About: The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference.

Changes:

added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes

generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used


Logo r-cran-pamr 1.54

by r-cran-robot - April 1, 2013, 00:00:06 CET [ Project Homepage BibTeX Download ] 41060 views, 8020 downloads, 0 subscriptions

About: Pam

Changes:

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


Logo JMLR LPmade 1.2.2

by rlichten - April 2, 2012, 17:11:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39944 views, 13123 downloads, 0 subscriptions

About: Link Prediction Made Easy

Changes:

v1.2.2

  • Fixed MAJOR issue related to github migration several months ago. The original github commit neglected to import empty folders. This caused parts of the project compilation procedure to fail. Any users of LPmade who downloaded the most recent version from github over the last several months would have encountered this build error and should download the most recent version. This change updates the network library makefile to create the empty folders and gets around the issue. Very sorry to anybody that this may have inconvenienced, but thanks for hanging in there if you diagnosed and solved it yourself.

  • Fixed issue with auroc on 32-bit architectures that caused integer wraparounds that produced incorrect results.


Logo JMLR Jstacs 2.3

by keili - September 13, 2017, 14:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39810 views, 9088 downloads, 0 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes and packages:

  • Jstacs 2.3 is the first release to be accompanied by JstacsFX, a library for building JavaFX-based graphical user interfaces based on JstacsTools
  • new interface MultiThreadedFunction
  • new class LargeSequenceReader for reading large sequence files in chunks
  • new interface QuickScanningSequenceScore
  • new class RegExpValidator for checking String inputs against a regular expression
  • new class IUPACDNAAlphabet

New features and improvements:

  • Alignments may now handle different costs for insert and delete gaps
  • ListResults may now be constructed from Collections of ResultSets
  • Several minor improvements and bugfixes in many classes
  • Improvements of documentation of several classes

Logo JMLR Shark 2.3.0

by igel - October 24, 2009, 22:12:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39483 views, 7248 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-RWeka 0.4-10

by r-cran-robot - January 10, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 39374 views, 8828 downloads, 0 subscriptions

About: R/Weka interface

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.330277


Logo JMLR MSVMpack 1.5.1

by lauerfab - March 9, 2017, 12:29:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39169 views, 10762 downloads, 0 subscriptions

About: MSVMpack is a Multi-class Support Vector Machine (M-SVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

Changes:
  • Fix compilation error with recent gcc

Logo peewit 0.10

by lorenz - May 7, 2014, 16:04:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39025 views, 7383 downloads, 0 subscriptions

About: peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current version-number is 0.10.

Changes:

v-cube with side-cubes


Logo JMLR Mulan 1.5.0

by lefman - February 23, 2015, 21:19:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37810 views, 10880 downloads, 0 subscriptions

About: Mulan is an open-source Java library for learning from multi-label datasets. Multi-label datasets consist of training examples of a target function that has multiple binary target variables. This means that each item of a multi-label dataset can be a member of multiple categories or annotated by many labels (classes). This is actually the nature of many real world problems such as semantic annotation of images and video, web page categorization, direct marketing, functional genomics and music categorization into genres and emotions.

Changes:

Learners

  • MLCSSP.java: Added the MLCSSP algorithm (from ICML 2013)
  • Enhancements of multi-target regression capabilities
  • Improved CLUS support
  • Added pairwise classifier and pairwise transformation

Measures/Evaluation

  • Providing training data in the Evaluator is unnecessary in the case of specific measures.
  • Examples with missing ground truth are not skipped for measures that handle missing values.
  • Added logistics and squared error losses and measures

Bug fixes

  • IndexOutOfBounds in calculation of MiAP and GMiAP
  • Bug fix in Rcut.java
  • When in rank/score mode the meta-data contained additional unecessary attributes. (Newton Spolaor)

API changes

  • Upgrade to Java 7
  • Upgrade to Weka 3.7.10

Miscalleneous

  • Small changes and improvements in the wrapper classes for the CLUS library
  • ENTCS13FeatureSelection.java (new experiment)
  • Enumeration is now used for specifying the type of meta-data. (Newton Spolaor)

Logo ELKI 0.7.1

by erich - March 14, 2016, 13:44:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37716 views, 6702 downloads, 0 subscriptions

About: ELKI is a framework for implementing data-mining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods.

Changes:

Additions and improvements from ELKI 0.7.0 to 0.7.1:

Algorithm additions:

  • GriDBSCAN: DBSCAN using grid partitioning (Minkowski distances only)

  • Compare-Means and Sort-Means k-means variations (much faster than traditional k-means)

  • Visualization of dendrograms.

Important bug fixes:

  • Classes with no package ("default package") would cause errors.

  • The fast power function implementation was sometimes returning incorrect results.

  • Random sampling was sometimes not sampling from the full data set.

UI improvements:

  • The file input source will now automatically choose the Arff parser for .arff files.

  • MiniGUI now allows choosing other applications.

  • MiniGUI now displays the command line in a separate field.

  • MiniGUI displays an error message, if an incorrect classpath or JAyatana (on Ubuntu) is detected.

  • Export to png now works, we added a work-around for an open Batik bug.

Smaller changes:

  • Many smaller bug fixes.

  • C-Index for cluster evaluation now can process larger data sets.

  • OPTICS output of undefined reachability fixed.

  • External distance matrixes are easier to use and perform additional checks.

  • Precomputed distance matrixes can answer range and kNN queries.

  • Voronoi visualization can be switched in the menu now.

  • Improved backwards command line compatibility with additional aliases.

  • Added generated @since annotations in JavaDoc.

  • Many new unit tests, renamed to the Java conventions.

  • Low-level reading of service files, to have faster startup.


Logo gensim 0.8.6

by Radim - December 9, 2012, 13:15:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 36451 views, 7459 downloads, 0 subscriptions

About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory).

Changes:
  • added the "hashing trick" (by Homer Strong)
  • support for adding target classes in SVMlight format (by Corrado Monti)
  • fixed problems with global lemmatizer object when running in parallel on Windows
  • parallelization of Wikipedia processing + added script version that lemmatizes the input documents
  • added class method to initialize Dictionary from an existing corpus (by Marko Burjek)

Logo JMLR Continuous Time Bayesian Network Reasoning and Learning Engine 1.1.1

by cshelton - December 9, 2013, 18:44:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 36450 views, 11964 downloads, 0 subscriptions

About: The CTBN-RLE is a C++ package of executables and libraries for inference and learning algorithms for continuous time Bayesian networks (CTBNs).

Changes:

compilation problems fixed


Logo Libra 1.1.2d

by lowd - February 4, 2016, 08:51:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 35763 views, 7461 downloads, 0 subscriptions

About: The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, arithmetic circuits, and mixtures of trees.

Changes:

Version 1.1.2d (12/29/2015):

  • Minor fixes to scripts
  • Published in JMLR ML-OSS!

Logo r-cran-penalized 0.9-42

by r-cran-robot - November 6, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 35013 views, 7681 downloads, 0 subscriptions

About: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.939105


Showing Items 41-60 of 674 on page 3 of 34: Previous 1 2 3 4 5 6 7 8 Next Last