Projects supporting the csv data format.
Showing Items 1-20 of 64 on page 1 of 4: 1 2 3 4 Next

Logo MLweb 1.1

by lauerfab - November 10, 2017, 11:34:48 CET [ Project Homepage BibTeX Download ] 12664 views, 3021 downloads, 3 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 gaxpy() and documentation on in-place operations
  • Add loo() function to Classifier and Regression models
  • New contributed toolbox for RNN
  • Minor fixes

Logo HIERDENC 1.0

by billandreo - October 31, 2017, 16:01:32 CET [ Project Homepage BibTeX Download ] 1044 views, 1090 downloads, 2 subscriptions

About: This is a tool for retrieving nearest neighbors and clustering of large categorical data sets represented in transactional form. The clustering is achieved via a locality-sensitive hashing of categorical datasets for speed and scalability.

Changes:

Initial Announcement on mloss.org.


Logo JMLR dlib ml 19.7

by davis685 - September 17, 2017, 15:10:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 205198 views, 31851 downloads, 5 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

Changes:

This release upgrades dlib's CNN+MMOD object detector to support creating multi-class detectors. It also includes significant speed improvements, allowing the detector to run at 98fps when executed on a NVIDIA 1080ti GPU. This release also adds a new 5 point face landmarking model that is over 10x smaller than the 68 point model, runs faster, and works with both HOG and CNN generated face detections. It is now the recommended landmarking model to use for face alignment.


Logo JMLR MLPACK 2.2.5

by rcurtin - August 26, 2017, 06:07:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 93655 views, 16780 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:

Released August 25, 2017.

  • Compilation fix for some systems (#1082).

  • Fix PARAM_INT_OUT() (#1100).


Logo python weka wrapper3 0.1.3

by fracpete - August 23, 2017, 01:18:36 CET [ Project Homepage BibTeX Download ] 4405 views, 966 downloads, 3 subscriptions

About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added check_for_modified_class_attribute method to FilterClassifier class
  • added complete_classname method to weka.core.classes module, which allows completion of partial classnames like .J48 to weka.classifiers.trees.J48; if there is a unique match; JavaObject.new_instance and JavaObject.check_type now make use of this functionality, allowing for instantiations like Classifier(cls=".J48")
  • jvm.start(system_cp=True) no longer fails with a KeyError: 'CLASSPATH' if there is no CLASSPATH environment variable defined
  • Libraries mtl.jar, core.jar and arpack_combined_all.jar were added as is to the weka.jar in the 3.9.1 release instead of adding their content to it. Repackaged weka.jar to fix this issue.

Logo python weka wrapper 0.3.11

by fracpete - August 23, 2017, 01:17:24 CET [ Project Homepage BibTeX Download ] 54635 views, 10954 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added check_for_modified_class_attribute method to FilterClassifier class
  • added complete_classname method to weka.core.classes module, which allows completion of partial classnames like .J48 to weka.classifiers.trees.J48; if there is a unique match; JavaObject.new_instance and JavaObject.check_type now make use of this functionality, allowing for instantiations like Classifier(cls=".J48")
  • jvm.start(system_cp=True) no longer fails with a KeyError: 'CLASSPATH' if there is no CLASSPATH environment variable defined
  • Libraries mtl.jar, core.jar and arpack_combined_all.jar were added as is to the weka.jar in the 3.9.1 release instead of adding their content to it. Repackaged weka.jar to fix this issue.

Logo KeLP 2.2.1

by kelpadmin - August 7, 2017, 17:20:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19833 views, 4155 downloads, 3 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code.

Changes:

In addition to minor bug fixes, this release includes:

  • A new cache (FixSizeKernelCache) that can store a larger number of computations.

  • Evaluators for measuring the quality of Clustering algorithms.

Furthermore we also released the new module kelp-input-generator, that contains the facilities to parse text snippets and generate tree representations for KeLP!

Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.2.1!


Logo SparklingGraph 0.0.7

by riomus - May 22, 2017, 15:29:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7587 views, 1632 downloads, 3 subscriptions

About: Large scale, distributed graph processing made easy.

Changes:

Graph partitioning methods APSP approximation method Performance improvements License change Bug fixes


Logo DynaML 1.4.1

by mandar2812 - April 20, 2017, 18:32:33 CET [ Project Homepage BibTeX Download ] 1142 views, 291 downloads, 1 subscription

About: DynaML is a Scala environment for conducting research and education in Machine Learning. DynaML comes packaged with a powerful library of classes implementing predictive models and a Scala REPL where one can not only build custom models but also play around with data work-flows.

Changes:

Initial Announcement on mloss.org.


Logo Armadillo library 7.800

by cu24gjf - March 8, 2017, 10:11:25 CET [ Project Homepage BibTeX Download ] 123184 views, 23640 downloads, 5 subscriptions

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About: Armadillo is a high quality C++ linear algebra library, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).

Changes:
  • more accurate sparse eigen decomposition by eigs_sym() and eigs_gen()
  • more robust handling of non-square matrices by lu()
  • expanded qz() to optionally specify ordering of the Schur form
  • expanded .each_slice() in the Cube class to support matrix multiplication
  • expanded several functions to handle sparse matrices
  • added expmat_sym(), logmat_sympd(), sqrtmat_sympd() for handling symmetric matrices
  • added polyfit() and polyval() for polynomial fitting
  • fix for aliasing issue in convolution functions conv() and conv2()
  • fix for memory leak in the field class when compiling in C++11/C++14 mode

Logo ADENINE 0.1.4

by samuelefiorini - February 17, 2017, 14:50:49 CET [ Project Homepage BibTeX Download ] 2929 views, 679 downloads, 2 subscriptions

About: ADENINE (A Data ExploratioN pIpeliNE) is a machine learning framework for data exploration that encompasses state-of-the-art techniques for missing values imputing, data preprocessing, unsupervised feature learning and clustering tasks.

Changes:
  • Adenine can now distribute the execution of its pipelines on multiple machines via MPI
  • kNN data imputing strategy is now implemented
  • added python 2.7 and 3.5 support
  • stability improved and bug fixed

Logo NaN toolbox 3.1.2

by schloegl - January 22, 2017, 12:24:59 CET [ Project Homepage BibTeX Download ] 73137 views, 13605 downloads, 3 subscriptions

About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values.

Changes:

Changes in v.3.1.2 - improve configuration and build system - support of more platforms (including Octave 4.2.0) improved

Changes in v.3.0.3 - improve compatibility for Octave on Windows

Changes in v.3.0.1 - fix packaging for octave

Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos

For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG


Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - January 16, 2017, 18:10:57 CET [ Project Homepage BibTeX Download ] 4494 views, 1116 downloads, 3 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org. Added GitHub page.


Logo Java Statistical Analysis Tool 0.0.7

by EdwardRaff - January 15, 2017, 22:21:50 CET [ Project Homepage BibTeX Download ] 3934 views, 967 downloads, 2 subscriptions

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

Changes:

See github release tab for change info


Logo ADAMS 16.12.1

by fracpete - December 22, 2016, 05:24:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 31945 views, 5762 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 DIANNE 0.5.0

by sbohez - October 25, 2016, 19:51:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2254 views, 478 downloads, 3 subscriptions

About: DIANNE is a modular software framework for designing, training and evaluating artificial neural networks on heterogeneous, distributed infrastructure . It is built on top of OSGi and AIOLOS and can transparently deploy and redeploy (parts of) a neural network on multiple machines, as well as scale up training on a compute cluster.

Changes:

Initial Announcement on mloss.org.


Logo JMLR JKernelMachines 3.0

by dpicard - May 4, 2016, 17:53:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 44229 views, 9338 downloads, 4 subscriptions

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About: machine learning library in java for easy development of new kernels and kernel algorithms

Changes:

Version 3.0

/! Warning: this version is incompatible with previous code

  • change license to BSD 3-clauses
  • change package name to net.jkernelmachines
  • change to maven build system (available through central)
  • online training interfaces to allow continuous online learning
  • add a new budget oriented kernel classifier
  • new kernel and processing especially for strings

Logo QMiner 5.0.0

by blazfortuna - April 8, 2016, 14:17:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4831 views, 868 downloads, 2 subscriptions

About: Analytic engine for real-time large-scale streams containing structured and unstructured data.

Changes:

Initial Announcement on mloss.org.


Logo JaTeCS 1.0.0

by aesuli - April 5, 2016, 17:23:12 CET [ Project Homepage BibTeX Download ] 3359 views, 740 downloads, 2 subscriptions

About: Jatecs is an open source Java library focused on automatic text categorization.

Changes:

Initial Announcement on mloss.org.


Logo ELKI 0.7.1

by erich - March 14, 2016, 13:44:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30374 views, 5244 downloads, 4 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.


Showing Items 1-20 of 64 on page 1 of 4: 1 2 3 4 Next