Best Machine Learning Libraries for Java


Here we list down 10 best machine learning libraries for Java, which have been compiled based on their popularity level from various websites, blogs and forums.

  1. ADAMS

Adams is a short form of advanced data mining and machine learning system. Adam is designed to build rapid and maintainable real world complex workflows. Adams is released under GPLv3.To control data flows in workflow Adams using tree like structure. This means that there are no explicit connections that are necessary.

Features of ADAMS Java Machine Learning Library

  • Machine learning
  • data mining
  • Data processing
  • Streaming
  • Spreadsheets
  • Databases
  • Imaging
  • Graphics support
  • Audio
  • Spectral data
  • Visualization
  • Scripting
  1. Deeplearning4j

Deeplearning4java is an open source machine learning library for java It is basically written in java and offers computing framework with a wide support for deep learning algorithms. Deeplearning4java is distributed deep learning library brought together with an intention to bring deep neural networks and deep reinforcement learning together for business environments. Deeplearning4java has ability to handle virtually unlimited simultaneous tasks.

Deeplearning4java is also serves as Do It Yourself tool for java. It can also be used i time series data for detection of anomalies like financial transactions. Rather than as a Research tool it is designed to used as business environments.

Features of Deeplearning4j Java Machine Learning Library

  • Layers
  • Losses
  • Activation
  • Initializer
  • Regularizer
  • Constraints
  • Metrics
  • Optimizer
  1. ELKI

ELKI, short for Environment for Developing KDD-Applications Supported by Index-structure, is written in java. It is basically an open source data mining  software. It is designed for students and researchers.

Elki Provide us a decent amount of highly configurable algorithm parameters. It is Knowledge discovery in data (KDD) framework allowed to advanced data mining algorithms for research. ELKI also allows the file format, distance measurements and similarity measurement.

ELKI is software framework used by graduates and teacher for their researches.

read more about ELKI here.

  1. JavaML

Java Ml is a API with huge collection of data mining and machine learning algorithms to implement with java. It is basically developed for researchers as well as software developers. JavaML has no GUI but simple and clear interface of every algorithm. It interface in very simple and easy to use. It is also written in java.

With the comparison of other clustering algorithms it allows to implement new algorithm very easy and clean way. The documentation and implementation of algorithm is clearly written and well documented.

To Know more about JavaMl, You can find it here.

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