opensearch-project / ml-commons
ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch.
Summary
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| Main Code: 6,643 LOC (130 files) = JAVA (99%) + POLICY (<1%) Secondary code: Test: 5,050 LOC (77); Generated: 0 LOC (0); Build & Deploy: 470 LOC (8); Other: 127 LOC (7); |
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| Duplication: 4% | |||
| File Size: 0% long (>1000 LOC), 83% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 63% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 79% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (14 components) | ||
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10 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
9 files |
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Latest commit date: 2022-01-28
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14
commits
(30 days)
4
contributors
(30 days) |
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