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Analyzed 2 days ago. based on code collected 2 days 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

Apache License 2.0
Permitted

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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
76%
Scala
13%
9 Other
11%

30 Day Summary

May 20 2021 — Jun 19 2021

12 Month Summary

Jun 19 2020 — Jun 19 2021
  • 102 Commits
    Down -155 (60%) from previous 12 months
  • 11 Contributors
    Up + 5 (83%) from previous 12 months