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Logo Obandit 0.2

by fre - November 6, 2017, 14:33:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1777 views, 433 downloads, 2 subscriptions

About: Obandit is an Ocaml module for multi-armed bandits. It supports the EXP, UCB and Epsilon-greedy family of algorithms.

Changes:

Initial Announcement on mloss.org.


Logo HIERDENC 1.0

by billandreo - October 31, 2017, 16:01:32 CET [ Project Homepage BibTeX Download ] 3156 views, 2742 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 Accord.NET Framework 3.8.0

by cesarsouza - October 23, 2017, 20:50:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 47935 views, 8190 downloads, 2 subscriptions

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details.

Changes:

For a complete list of changes, please see the full release notes at the release details page at:

https://github.com/accord-net/framework/releases/tag/v3.8.0


Logo bufferkdtree 1.3

by fgieseke - October 20, 2017, 11:39:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1442 views, 327 downloads, 2 subscriptions

About: The bufferkdtree package is a Python library that aims at accelerating nearest neighbor computations using both k-d trees and modern many-core devices such as graphics processing units (GPUs).

Changes:

Initial Announcement on mloss.org.


Logo r-cran-effects 4.0-0

by r-cran-robot - September 14, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 2096 views, 531 downloads, 1 subscription

About: Effect Displays for Linear, Generalized Linear, and Other Models

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.810965


Logo JMLR Jstacs 2.3

by keili - September 13, 2017, 14:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37836 views, 8689 downloads, 4 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes and packages:

  • Jstacs 2.3 is the first release to be accompanied by JstacsFX, a library for building JavaFX-based graphical user interfaces based on JstacsTools
  • new interface MultiThreadedFunction
  • new class LargeSequenceReader for reading large sequence files in chunks
  • new interface QuickScanningSequenceScore
  • new class RegExpValidator for checking String inputs against a regular expression
  • new class IUPACDNAAlphabet

New features and improvements:

  • Alignments may now handle different costs for insert and delete gaps
  • ListResults may now be constructed from Collections of ResultSets
  • Several minor improvements and bugfixes in many classes
  • Improvements of documentation of several classes

About: Tool aimed at helping remedy the reproducibility problem, specifically in the statistical and data wrangling aspects.

Changes:

Initial Announcement on mloss.org.


Logo Top Frequency Based Parallel Coordinates 1.0.0

by matloff - September 5, 2017, 05:49:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1838 views, 393 downloads, 1 subscription

About: A novel method to create parallel coordinates plots on large data sets without causing a "black screen" problem.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-CORElearn 1.51.2

by r-cran-robot - August 8, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 27386 views, 5469 downloads, 2 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.164852


About: A non-iterative, incremental and hyperparameter-free learning method for one-layer feedforward neural networks without hidden layers. This method efficiently obtains the optimal parameters of the network, regardless of whether the data contains a greater number of samples than variables or vice versa. It does this by using a square loss function that measures errors before the output activation functions and scales them by the slope of these functions at each data point. The outcome is a system of linear equations that obtain the network's weights and that is further transformed using Singular Value Decomposition.

Changes:

Initial Announcement on mloss.org.


Showing Items 41-50 of 673 on page 5 of 68: Previous 1 2 3 4 5 6 7 8 9 10 Next Last