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Editor to share with you what are the Java machine learning tools and libraries. I hope you will get something after reading this article. Let's discuss it together.

1. Weka integrates machine learning algorithms for data mining. These algorithms can be applied directly to a dataset or you can write your own code to call them. Weka includes a series of tools, such as data preprocessing, classification, regression, clustering, association rules and visualization.

2.Massive Online Analysis (MOA) is a popular open source framework for data stream mining and has a very active growing community. It includes a series of machine learning algorithms (classification, regression, clustering, anomaly detection, concept drift detection and recommendation system) and evaluation tools. Associated with the WEKA project, MOA is also written in Java, which is more extensible.

The 3.MEKA project provides an open source implementation for multi-tag learning and evaluation methods. In multi-label classification, we want to predict multiple output variables for each input instance. This is different from a "normal" situation where only a single target variable is involved. In addition, MEKA is based on WEKA's machine learning toolkit.

4. Advanced Data mining And Machine learning System (ADAMS) is a new type of flexible workflow engine, which aims to quickly establish and maintain complex knowledge flows in the real world. It is based on GPLv3.

5. Environment for Developing KDD-Applications Supported by Index-Structure (ELKI) is an open source (AGPLv3) data mining software based on Java. ELKI mainly focuses on algorithm research, focusing on unsupervised methods and anomaly detection in clustering analysis.

6. Mallet is a text file-oriented machine learning toolkit based on Java. Mallet supports classification algorithms such as * entropy, naive Bayesian and decision tree classification.

7. Encog is an advanced machine learning framework, which integrates support vector machine (SVM), artificial neural network, genetic algorithm, Bayesian network, hidden Markov model (HMM), genetic programming and genetic algorithm.

8. The Datumbox machine learning framework is an open source framework written in Java that allows the rapid development of machine learning and statistical applications. The core focus of the framework includes a large number of machine learning algorithms and statistical tests, which can deal with medium-sized data sets.

9. Deeplearning4j is a commercial, open source, distributed in-depth learning library written in Java and Scala. It is designed to be used in a business environment, not as a research tool.

10. Mahout is a machine learning framework with built-in algorithms. Mahout-Samsara helps people create their own math and provides some off-the-shelf algorithm implementations.

11.Rapid Miner was developed by Dortmund University of Technology in Germany. It provides a GUI (graphical user interface) and Java API for developers to develop applications. It also provides some machine learning algorithms for data processing, visualization and modeling.

12. Apache SAMOA is a machine learning (ML) framework that embeds programming abstractions for distributed stream ML algorithms and allows the development of new ML algorithms without directly dealing with the complexity of the underlying distributed stream processing engines (DSPEe, such as Apache Storm, Apache S4, and Apache samza). Users can develop distributed stream ML algorithms and execute them on multiple DSPEs.

13. Neuroph simplifies neural network development by providing Java network libraries and GUI tools that support the creation, training, and preservation of neural networks.

14. Oryx 2 is an implementation of the Lambda architecture based on Apache Spark and Apache Kafka, but has gradually become specialized with real-time large-scale machine learning. This is a framework for building applications, but also includes packaging, and end-to-end applications for collaborative filtering, classification, regression, and clustering.

15. Stanford Classifier is a machine learning tool that classifies data items into a category. A probability classifier, such as this one, can give the probability distribution of a class assignment to a data item. The software is an Java implementation of entropy classifier.

16.io is a Retina API with fast and accurate brain-like natural language processing algorithms.

17.JSAT is a quick start machine learning library. The library was developed by me in my spare time and released based on GPL3. A part of the library can be learned independently, for example, all the code is independent. JSAT has no external dependencies and is written in pure Java.

18. N-Dimensional Arrays for Java (ND4J) is a scientific computing library for JVM. They are used in a production environment, indicating that routines are designed to run with minimal memory requirements.

19. Java Machine Learning Library (Java Machine Learning Library) is the related implementation of a series of machine learning algorithms. These algorithms, whether source code or documentation, are well written. Its main language is Java.

20. Java-ML is a Java API of a series of machine learning algorithms written in Java. It only provides a standard algorithm interface.

21. MLlib (Spark) is the extensible machine learning library of Apache Spark. Although it is Java, the library also supports Java,Scala and Python binding with the platform. This library is *, and there are many algorithms.

twenty-two。 H2O is a machine learning API for intelligent applications. It scaled statistics, machine learning and mathematics on big data. H2O is extensible, and developers can use simple mathematical knowledge in the core.

23. WalnutiQ is a partial object-oriented model of human brain, which has a commonly used learning algorithm in theory (it is being studied in the direction of simple and strong emotional artificial intelligence model).

24. RankLib is a ranking learning algorithm library. At present, eight popular algorithms have been implemented.

25. Htm.java (implementation of Hierarchical Temporal Memory algorithm based on Java) is a Java interface of Numenta platform for intelligent computing. Source code

After reading this article, I believe you have a certain understanding of "what are the Java machine learning tools and libraries". If you want to know more about it, you are welcome to follow the industry information channel. Thank you for your reading!

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