Showing 6 open source projects for "statistical learning"

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    PyMC

    PyMC

    Bayesian Modeling and Probabilistic Programming in Python

    PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.
    Downloads: 0 This Week
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    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is...
    Downloads: 6 This Week
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  • 3
    stkpp

    stkpp

    C++ Statistical ToolKit

    STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template...
    Downloads: 0 This Week
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  • 4
    Adaptive Gaussian Filtering

    Adaptive Gaussian Filtering

    Machine learning with Gaussian kernels.

    Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities.
    Downloads: 0 This Week
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  • 5

    Chordalysis

    Log-linear analysis (data modelling) for high-dimensional data

    ===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures,...
    Downloads: 0 This Week
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  • 6
    Myrtle

    Myrtle

    A simple programmable spreadsheet for learning statistics.

    Myrtle is a simple programmable spreadsheet and statistical analysis software specifically designed for learning statistics. It provides the standard spreadsheet functionality one would expect like multiple tabbed sheets, relative and absolute row and column referencing in formulas, and a large catalog of built-in functions. Functions specific to logic and computer science, mathematics, probability, and statistics are available.
    Downloads: 1 This Week
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