Search Results for "numerical analysis"
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Showing 5 open source projects for "numerical analysis"
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify... -
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Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.
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Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.
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kombinatoriC delta library
CAS Algorithms embeded as libraries.
Personal research achievements from the authors presented here in the form of symbolic Algebra and non-numerical analysis algorithms implemented in C/C++, Java, and/or Pascal. As part of a more wide, simple, powerful and robust CAS enviroment under development, new code will be continuously added up to this repository. The authors give their welcome and encouragement to everyone interested in bring some kind of collaboration.
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