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81 projects in result set
Dernière Mise à Jour: 2014-06-02 01:05

Armadillo C++ Library

Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. The API is deliberately similar to Matlab's. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS numerics libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries.

Dernière Mise à Jour: 2014-03-16 18:01

SOFA Statistics

SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learning as you go, and beautiful output. SOFA can connect directly to your database and lets you display results in an attractive format ready to share or put in a spread­sheet. SOFA will help you learn as you go, whether you are a student, business analyst, or researcher.

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Environnement de base de données: MySQL, PostgreSQL (pgsql), SQLite
Langage naturel: Breton, Croatian, English, Galician, Spanish
Système d'exploitation: Linux, Windows
Langage de programmation: Python
Interface utilisateur: wxWidgets
Dernière Mise à Jour: 2012-11-06 23:43

Shared Scientific Toolbox in Java

The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.

Dernière Mise à Jour: 2014-04-18 21:59

arbtt

The program arbtt, the automatic rule-based time tracker, allows you to investigate how you spend your time, without having to manually specify what you are doing. arbtt records which windows are open and active, and provides you with a powerful rule-based language to afterwards categorize your work.

Dernière Mise à Jour: 2012-09-25 21:55

Strategico

Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.

Dernière Mise à Jour: 2019-07-25 03:13

R Portable

R portableは、コンピュータ上にRの構成物を置かずサムドライブやポータブルハードディスク上から実行できるよう、RをPortableApps frameworkで動くようにします。

Dernière Mise à Jour: 2008-08-14 19:31

Math.NET

Math.NET 目指す自己シンボリック数学 (コンピューター代数学システム) とパーサーと線形代数学、複素微分解析、システム解決およびサポートを含む、数値/科学的な計算のためのきれいなフレームワークに含まれる

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Dernière Mise à Jour: 2014-06-05 19:02

Morpho

ランドマークの分析を実行する R パッケージに基づく幾何学的な形態。インストール手順: https://sourceforge.net/p/morpho-rpackage/wiki/Installation_Morpho/よくあるご質問: https://sourceforge.net/p/morpho-rpackage/wiki/FAQ/変更履歴: https://github.com/zarquon42b/Morpho/releases

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Dernière Mise à Jour: 2014-01-07 23:16

MLPACK

MLPACK is a C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression and least-angle regression.

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Dernière Mise à Jour: 2014-02-12 22:36

superseriousstats

superseriousstats is a small and efficient program for creating a Web page with statistics from various types of IRC logs. It keeps track of its parse history and only processes new activity before storing any accumulated data in a SQLite or MySQL database. It is suitable for high volume IRC channels and large log archives, and is relatively easy to integrate with IRC services (e.g. bots) that interact with the database and provide last seen information and many other statistics directly in your channel.

Environnement de base de données: MySQL
Langage naturel: English
Système d'exploitation: OS Independent
Langage de programmation: PHP
Dernière Mise à Jour: 2012-06-01 22:13

pepper

pepper is a commandline tool for retrieving statistics and generating reports from source code repositories. It ships with several graphical and textual reports, and is easily extensible using the Lua scripting language. It includes support for multiple version control systems, including Git and Subversion.

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Dernière Mise à Jour: 2012-11-06 10:42

Accord.NET Framework

Accord.NET provides statistical analysis, machine learning, image processing, and computer vision methods for .NET applications. The Accord.NET Framework extends the popular AForge.NET with new features, adding to a more complete environment for scientific computing in .NET.

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Dernière Mise à Jour: 2010-10-27 17:20

n2

n2 is a client/server system for transmitting forensic snapshots from a number of hosts to a receiver node. This receiver collects statistics and is able to present an overview of the current and historical situation on a server. n2 provides a robust solution for real-time monitoring, optimizing performance, and analyzing crashes.

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Système d'exploitation: Linux
Langage de programmation: C, C++, JavaScript
Interface utilisateur: Web Environment
Dernière Mise à Jour: 2013-04-03 11:29

Keyfrog

KeyFrog monitors the keyboard and visualizes its
usage statistics. The user can obtain much
information about keyboard activity: the intensity
of keyboard usage, how was it distributed in time,
which applications were used, etc. This may be
very useful, for example, to developers to monitor
their productivity. The environment being monitored is the X Window System (text applications are explicitly supported if run inside an X terminal).

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