Open Source Python Information Analysis Software
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Python Information Analysis Software
View 204 business solutionsBrowse free open source Python Information Analysis Software and projects below. Use the toggles on the left to filter open source Python Information Analysis Software by OS, license, language, programming language, and project status.
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GDL - GNU Data Language, a free IDL (Interactive Data Language, see http://ittvis.com/idl/) compatible incremental compiler.
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Augustus
PMML-compliant scoring engine and analytic toolkit
Augustus development has moved to google code. The new project page is augustus.googlecode.com. New releases of the project are not currently being released to sourceforge. Augustus is designed for statistical and data mining models and produces and consumes models with 10,000s of segments. Versions of Augustus support PMML 3, 4.0.1, and 4.1. -
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clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.
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ConDEnSE (Confidential Data Enabled Statistical Exploration) will be a web-based environment for statistical analysis of confidential data from various database sources, based on Plone and R, and using the Jackknife method of confidentiality protection.
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ExpLab is a set of tools that supports the running, documentation and evaluation of computational experiments.
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This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.
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Everyday Software for the Researcher of Restricted Means: This project is intended to offer scientists and students with small budgets advanced versions of aqua-built desktop-editing, graphics and statistical applications for MacOSX.
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slycat
Web-based data science analysis and visualization platform.
This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data.
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