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Weka

Weka is a collection of machine learning algorithms for data mining tasks

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Overview

Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. - Official website

Weka(Waikato Environment for Knowledge Analysis) provides access to deep learning with WekaDeeplearning4j which uses Deeplearning4j.

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Platform

   

Social

 

System Requirements

#Recommended
1Java v8

Ratings

Aggregate
4.58 
 5
Capterra4 
 5		based on 7 reviews
Class Central4.8 
 5		based on 19 reviews
G2CROWD4.5 
 5		based on 10 reviews
SourceForge5 
 5		based on 50 reviews

Developer

Eibe Frank, Mark Hall, Peter Reutemann, Len Trigg, University of Waikato

Written in

Java

Initial Release

1 May 2000

Repository

https://github.com/Waikato/weka-3.8, https://github.com/Waikato/weka-trunk

License

GPL v2 for v3.6, GPL v3 for v3.7.5+

Categories

Machine Learning, Data Mining, Deep Learning, Framework

Alternatives

Machine Learning
Apache Mahout   Apache MXNet (Incubating)   Apache Spark   Apache SystemML   Eclipse Deeplearning4j   MALLET   Massive Online Analysis (MOA)   mlpack   OpenCV   Orange   scikit-learn   TensorFlow   The Microsoft Cognitive Toolkit   Torch   Yooreeka   PyTorch  
Data Mining
ELKI   Massive Online Analysis (MOA)   OpenNN   Orange   scikit-learn   Yooreeka  
Deep Learning
Apache MXNet (Incubating)   Apache SystemML   Caffe   Eclipse Deeplearning4j   OpenNN   TensorFlow   The Microsoft Cognitive Toolkit   Torch   PyTorch  

This page was last updated with commit: Fixed syntax in software source files (1e763e9)