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About: The package provides a Lagrangian approach to the posterior regularization of given linear mappings. This is important in two cases, (a) when systems are under-determined and (b) when the external model for calculating the mapping is invariant to properties such as scaling. The software may be applied in cases when the external model does not provide its own regularization strategy. In addition, the package allows to rank attributes according to their distortion potential to a given linear mapping.

Changes:

Version 1.1 (May 23, 2012) memory and time optimizations distderivrel.m now supports assessing the relevance of attribute pairs

Version 1.0 (Nov 9, 2011) * Initial Announcement on mloss.org.


About: TBEEF, a doubly ensemble framework for recommendation and prediction problems.

Changes:

Included the final technical report.


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 5049 views, 1095 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Logo MLweb 0.1.4

by lauerfab - June 28, 2016, 16:00:52 CET [ Project Homepage BibTeX Download ] 4721 views, 1093 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 Logistic Regression
  • Add support for sparse input in fast training of linear SVM
  • Better support for sparse vectors/matrices
  • Fix plot windows in IE
  • Minor bug fixes

Logo r-cran-ncvreg 2.5-0

by r-cran-robot - March 15, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 4878 views, 1092 downloads, 0 subscriptions

About: Regularization paths for SCAD- and MCP-penalized regression models

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.449164


Logo pboost 1.0

by nowozin - November 13, 2007, 08:48:28 CET [ Project Homepage BibTeX Download ] 4255 views, 1091 downloads, 0 subscriptions

About: The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of [...]

Changes:

Initial Announcement on mloss.org.


Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 3591 views, 1090 downloads, 1 subscription

About: Gaussian process RTS smoothing (forward-backward smoothing) based on moment matching.

Changes:

Initial Announcement on mloss.org.


Logo NuPIC 0.1

by rhyolight - August 21, 2013, 21:01:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2540 views, 1083 downloads, 1 subscription

About: The mission of this project is to build and support a community interested in machine learning and machine intelligence based on modeling the neocortex and the principles upon which it works.

Changes:

Initial Announcement on mloss.org.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5458 views, 1082 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo CPLVE 0.1

by wannesm - June 5, 2009, 13:06:42 CET [ BibTeX Download ] 3044 views, 1082 downloads, 1 subscription

About: Preparing

Changes:

Initial Announcement on mloss.org.


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