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Analyzed 5 months ago. based on code collected over 1 year ago.

Project Summary

Apache Mahout's goal is to build scalable machine learning libraries. With scalable we mean:
Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms

Tags

algorithms classifiers clustering collaborative_filtering datamining data_mining dimension_reduction distributed distributed_computing hadoop java library machinelearning machine_learning mapreduce recommender regression

In a Nutshell, Apache Mahout...

Apache License 2.0
Permitted

Commercial Use

Modify

Distribute

Place Warranty

Sub-License

Private Use

Use Patent Claims

Forbidden

Hold Liable

Use Trademarks

Required

Include Copyright

State Changes

Include License

Include Notice

These details are provided for information only. No information here is legal advice and should not be used as such.

Project Security

Vulnerabilities per Version ( last 10 releases )

There are no reported vulnerabilities

Project Vulnerability Report

Security Confidence Index

Poor security track-record
Favorable security track-record

Vulnerability Exposure Index

Many reported vulnerabilities
Few reported vulnerabilities

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About Project Security

Languages

Languages?height=75&width=75
Java
77%
Scala
13%
9 Other
10%

30 Day Summary

Dec 12 2018 — Jan 11 2019

12 Month Summary

Jan 11 2018 — Jan 11 2019
  • 10 Commits
    Down -243 (96%) from previous 12 months
  • 2 Contributors
    Down -15 (88%) from previous 12 months