Projects supporting the libsvm data format.


Logo KeLP 1.2.1

by kelpadmin - July 24, 2015, 15:43:13 CET [ Project Homepage BibTeX Download ] 2857 views, 726 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 classifiers without writing a single line of code.

Changes:

The code for learning relations between pairs of short texts has been released, and includes the approach described in:

Simone Filice, Giovanni Da San Martino and Alessandro Moschitti. Relational Information for Learning from Structured Text Pairs. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015.

In particular this new release includes:

  • TreePairRelTagger: a manipulator that establishes relations between two tree representations (available in the maven project discreterepresentation)

  • 5 new kernels on pairs: released in the maven project standard-kernel

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 1.2.1!


Logo python weka wrapper 0.3.2

by fracpete - June 28, 2015, 23:09:13 CET [ Project Homepage BibTeX Download ] 15727 views, 3385 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:
  • The "packages" parameter of the "weka.core.jvm.start()" function can be used for specifying an alternative Weka home directory now as well
  • added "train_test_split" method to "weka.core.Instances" class to easily create train/test splits
  • "evaluate_train_test_split" method of "weka.classifiers.Evaluation" class now uses the "train_test_split" method

Logo ADAMS 0.4.10

by fracpete - June 22, 2015, 23:14:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13439 views, 2756 downloads, 3 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows.

Changes:
  • fixes a glitch in the debugging functionality, when using the Breakpoint control actor

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 8579 views, 1689 downloads, 3 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

Changes:
  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version


Logo Somoclu 1.4.1

by peterwittek - January 28, 2015, 13:19:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8210 views, 1631 downloads, 2 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • Better support for ICC.
  • Faster code when compiling with GCC.
  • Building instructions and documentation improved.
  • Bug fixes: portability for R, using native R random number generator.

Logo JMLR JKernelMachines 2.5

by dpicard - December 11, 2014, 17:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 20019 views, 4663 downloads, 4 subscriptions

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

Changes:

Version 2.5

  • New active learning algorithms
  • Better threading management
  • New multiclass SVM algorithm based on SDCA
  • Handle class balancing in cross-validation
  • Optional support of EJML switch to version 0.26
  • Various bugfixes and improvements

Logo WolfeSVM 0.0

by utmath - November 19, 2014, 10:46:11 CET [ Project Homepage BibTeX Download ] 946 views, 246 downloads, 2 subscriptions

About: This is a library for solving nu-SVM by using Wolfe's minimum norm point algorithm. You can solve binary classification problem.

Changes:

Initial Announcement on mloss.org.


Logo LIBOL 0.3.0

by stevenhoi - December 12, 2013, 15:26:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11586 views, 4115 downloads, 2 subscriptions

About: LIBOL is an open-source library with a family of state-of-the-art online learning algorithms for machine learning and big data analytics research. The current version supports 16 online algorithms for binary classification and 13 online algorithms for multiclass classification.

Changes:

In contrast to our last version (V0.2.3), the new version (V0.3.0) has made some important changes as follows:

• Add a template and guide for adding new algorithms;

• Improve parameter settings and make documentation clear;

• Improve documentation on data formats and key functions;

• Amend the "OGD" function to use different loss types;

• Fixed some name inconsistency and other minor bugs.


Logo OpenANN 1.1.0

by afabisch - September 26, 2013, 23:52:03 CET [ Project Homepage BibTeX Download ] 3863 views, 823 downloads, 2 subscriptions

About: A library for artificial neural networks.

Changes:

Added algorithms:

  • L-BFGS optimizer
  • k-means
  • sparse auto-encoder
  • preprocessing: normalization, PCA, ZCA whitening

Logo Nen Beta

by pascal - February 19, 2012, 00:31:34 CET [ Project Homepage BibTeX Download ] 4077 views, 1175 downloads, 1 subscription

About: 3-layer neural network for regression with sigmoid activation function and command line interface similar to LibSVM.

Changes:

Initial Announcement on mloss.org.