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Logo Multi Annotator Supervised LDA for regression 1.0

by fmpr - January 16, 2017, 18:10:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1922 views, 303 downloads, 3 subscriptions

About: MA-sLDAr is a C++ implementation of the supervised topic models with response variables provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Multi Annotator Supervised LDA for classification 1.0

by fmpr - January 16, 2017, 18:01:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1503 views, 249 downloads, 3 subscriptions

About: MA-sLDAc is a C++ implementation of the supervised topic models with labels provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Java Statistical Analysis Tool 0.0.7

by EdwardRaff - January 15, 2017, 22:21:50 CET [ Project Homepage BibTeX Download ] 3617 views, 896 downloads, 2 subscriptions

About: General purpose Java Machine Learning library for classification, regression, and clustering.

Changes:

See github release tab for change info


Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 48427 views, 8435 downloads, 4 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

About: Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition

Changes:

Initial Announcement on mloss.org.


Logo ADAMS 16.12.1

by fracpete - December 22, 2016, 05:24:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30533 views, 5569 downloads, 3 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:

  • Over 80 new actors, nearly 30 new conversions
  • Weka Investigator -- the big brother of the Weka Explorer, or how to be more efficient with less clicks using multiple datasets in multiple sessions and multiple predefined outputs per evaluation run
  • Weka Multi-Experimenter -- simple interface for running Weka and ADAMS experiments.
  • File commander -- dual-pane file manager (inspired by Norton/Midnight commander) that allows you to manage local and remote files (ftp, sftp, smb); usually faster than native file managers (like Windows Explorer, Nautilus, Caja) in terms of handling 10s of thousand of files in a single directory
  • experimental deeplearning4j module
  • module for querying/consuming webservices using Groovy
  • basic terminal-based GUI for remote machines (eg cloud)
  • many interactive actors can be used in headless environment now as well
  • Fixed a memory leak introduced by Java's logging framework
  • Flow editor now has predefined rules for swapping actors, e.g. Trigger with Tee or ConditionalTrigger, maintaining as many options as possible (including any sub-actors).
  • improved imaging and PDF support

Logo WEKA 3.9.1

by mhall - December 19, 2016, 04:44:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 75184 views, 15914 downloads, 5 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

In core weka:

  • JAMA-based linear algebra routines replaced with MTJ. Faster operation with the option to use native libraries for even more speed
  • General efficiency improvements in core, filters and some classifiers
  • GaussianProcesses now handles instance weights
  • New Knowledge Flow implementation. Engine completely rewritten from scratch with a simplified API
  • New Workbench GUI
  • GUI package manager now has a search facility
  • FixedDictionaryStringToWordVector filter allows the use of an external dictionary for vectorization. DictionarySaver converter can be used to create a dictionary file

In packages:

  • Packages that were using JAMA are now using MTJ
  • New netlibNativeOSX, netlibNativeWindows and netlibNativeLinux packages providing native reference implementations (and system-optimized implementation in the case of OSX) of BLAS, LAPACK and ARPACK linear algebra
  • New elasticNet package, courtesy of Nikhil Kinshore
  • New niftiLoader package for loading a directory with MIR data in NIfTI format into Weka
  • New percentageErrorMetrics package - provides plugin evaluation metrics for root mean square percentage error and mean absolute percentage error
  • New iterativeAbsoluteErrorRegression package - provides a meta learner that fits a regression model to minimize absolute error
  • New largeScaleKernelLearning package - contains filters for large-scale kernel-based learning
  • discriminantAnalysis package now contains an implementation for LDA and QDA
  • New Knowledge Flow component implementations in various packages
  • newKnowledgeFlowStepExamples package - contains code examples for new Knowledge Flow API discussion in the Weka Manual
  • RPlugin updated to latest version of MLR
  • scatterPlot3D and associationRulesVisualizer packages updated with latest Java 3D libraries
  • Support for pluggable activation functions in the multiLayerPerceptrons package

Logo JMLR scikitlearn 0.18.1

by fabianp - November 28, 2016, 17:45:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32590 views, 12123 downloads, 5 subscriptions

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

Changes:

Update for 0.18 .1


Logo Tools for Regression and Classification 1.0.0

by matloff - October 29, 2016, 08:22:40 CET [ Project Homepage BibTeX Download ] 2134 views, 412 downloads, 3 subscriptions

About: Toolkit for parametric and nonparametric regression and classification.

Changes:

Initial Announcement on mloss.org.


Logo rectools a Novel Toolbox for Recommender Systems 1.0.0

by matloff - October 29, 2016, 07:41:58 CET [ Project Homepage BibTeX Download ] 1980 views, 427 downloads, 2 subscriptions

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(based on 1 vote)

About: Novel R toolbox for collaborative filtering recommender systems.

Changes:

Initial Announcement on mloss.org.


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