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
In a Nutshell, Apache Mahout...
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took an estimated 38 years of effort (COCOMO model)
starting with its first commit in January, 2008
ending with its most recent commit about 1 year ago
Quick Reference
Apache License 2.0
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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
Vulnerability Exposure Index
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30 Day SummaryJan 1 2025 — Jan 31 2025
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12 Month SummaryJan 31 2024 — Jan 31 2025
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