Machine Learning in Java by Bostjan Kaluza

Machine Learning in Java



Download Machine Learning in Java

Machine Learning in Java Bostjan Kaluza ebook
ISBN: 9781784396589
Format: pdf
Page: 227
Publisher: Packt Publishing, Limited


Weka has a collection of machine learning algorithms for data mining tasks. The library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. The Apache Mahout™ project's goal is to build an environment for quickly creating scalable performant machine learning applications. Datumbox is an open-source Machine Learning framework written in Java which allows the rapid development of Machine Learning and Statistical applications. Department of Computer Science. Download the second version if you already have Java 1.6 (or later) on your system. This method will return the score for the supplied feature index. This is a list of 25 Java Machine learning tools & libraries. This tutorial shows you how you can test the performance of a classifier on a data set. Typical usage of a feature scoring algorithm is shown in the snippet below. This paper introduces the Encog library for Java and C#, a scalable, adaptable, multi-platform machine learning framework that was first released in 2008. Machine Learning Algorithms in Java. Machine-learning-samples - Sample applications built using Amazon Machine Learning. This tutorial will introduce two classes. These executables will install Weka in your Program Menu.





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