Search Results for "data mining matlab"
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Showing 8 open source projects for "data mining matlab"
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GeoTools, the Java GIS toolkit
Toolkit for working with and mapping geospatial data
GeoTools is an open source (LGPL) Java code library which provides standards compliant methods for the manipulation of geospatial data. GeoTools is an Open Source Geospatial Foundation project. The GeoTools library data structures are based on Open Geospatial Consortium (OGC) specifications. -
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mksqlite
A MATLAB(R) Mex-DLL to SQLite Databases
Did you ever want to store your MATLAB(R) data in a SQL database? Nothing large, simply a few array or strutures in a few tables. Maybe a few indicies and everything manageable with SQL commands? Then msqlite will be the right choice for you! mksqlite connects the power of MATLAB(R) with the efficiency of the SQLite database engine. (See also https://github.com/AndreasMartin72/mksqlite) -
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Graph-RAT is a database abstraction layer designed to make it easy to use a large library of graph-analysis routines on a database as well as add new kinds of algorithms to data mining.
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primeHandle is a set of data management tools in support of the PrIMe Initiative (http://primekinetics.org). primeHandle includes graphical user interfaces for searching through data collections, editing and submitting data to the PrIMe Data Depository.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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HOT is a package of Matlab and Octave compatible functions that manage thermodynamic data for a wide range of species. Functions calculate almost all the most common thermodynamic quantities of mixtures. Python users may also want to look at PYroMat at https://chmarti1.github.io/PYroMat/index.html
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MiningMart is a graphical tool for transforming data from relational databases. It provides two dual graphical views on the transformations, a data view and a process view. The focus is on the preparation of data for data mining.
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