Encog:用于Java和c#的可互换机器学习模型库

Jeff Heaton
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引用次数: 78

摘要

本文介绍了用于Java和c#的Encog库,这是一个可扩展的、可适应的、多平台的机器学习框架,于2008年首次发布。Encog允许使用回归、分类和聚类将各种机器学习模型应用于数据集。各种支持的机器学习模型可以以最少的重新编码互换使用。Encog使用高效的多线程代码,通过利用现代多核处理器来减少训练时间。当前版本的Encog可以从这个http URL下载
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Encog: library of interchangeable machine learning models for Java and C#
This paper introduces the Encog library for Java and C#, a scalable, adaptable, multiplatform machine learning framework that was 1st released in 2008. Encog allows a variety of machine learning models to be applied to datasets using regression, classification, and clustering. Various supported machine learning models can be used interchangeably with minimal recoding. Encog uses efficient multithreaded code to reduce training time by exploiting modern multicore processors. The current version of Encog can be downloaded from this http URL
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