Showing 4 open source projects for "linear"

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    MongoDB Atlas runs apps anywhere

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    Enterprise-grade ITSM, for every business

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  • 1
    Apache HBase

    Apache HBase

    Get random, realtime read/write access to your Big Data

    Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache...
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  • 2

    wzd

    Powerful storage server, designed for big data storage systems

    wZD is a server written in Go language that uses a modified version of the BoltDB database as a backend for saving and distributing any number of small and large files, NoSQL keys/values, in a compact form inside micro Bolt databases (archives), with distribution of files and values in BoltDB databases depending on the number of directories or subdirectories and the general structure of the directories. Using wZD can permanently solve the problem of a large number of files on any POSIX...
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  • 3
    Universal Java Matrix Package

    Universal Java Matrix Package

    sparse and dense matrix, linear algebra, visualization, big data

    The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra such as matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported, too. The Universal Java Matrix Package provides various visualization methods, import and export filters for a large number of file formats, and even the possibility to link to JDBC databases. ...
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  • 4

    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, also known as chordal graphs. ...
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