Projects supporting the multiple representations format data format.


Logo KeLP 2.2.0

by kelpadmin - April 7, 2017, 16:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16139 views, 3522 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 learning algorithm that enable (for the first time in KeLP) to deal with sequences labeling problems! It is based on a Markovian formulation within a SVM framework. Most noticeably: this new meta-algorithm for sequence learning can deal both with linear algorithms and with kernel-based algorithms!

  • A new cache (SimpleDynamicKernelCache) has been added to avoid the need of specifying the number of expected items in the dataset. It is not specialized for any learning algorithm, so it is not the most efficient cache, but it is very easy to use.

Furthermore we also released a brand new web site www.kelp-ml.org, where you can find several tutorials and documentation about 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 2.2.0!


Logo SALSA.jl 0.0.5

by jumutc - September 28, 2015, 17:28:56 CET [ Project Homepage BibTeX Download ] 2242 views, 485 downloads, 1 subscription

About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the well-known stochastic algorithms for Machine Learning developed in the high-level technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and non-linear Support Vector Machines applied to large data samples with user-centric and user-friendly emphasis.

Changes:

Initial Announcement on mloss.org.


Logo MIPS, The migrant implementation system 1.0

by thomasfannes - April 28, 2015, 15:07:05 CET [ Project Homepage BibTeX Download ] 2585 views, 706 downloads, 3 subscriptions

About: MIPS is a software library for state-of-the-art graph mining algorithms. The library is platform independent, written in C++(03), and aims at implementing generic and efficient graph mining algorithms.

Changes:

description update