Details
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Improvement
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Status: Open
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Minor
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Resolution: Unresolved
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3.6.1
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None
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None
Description
It had been noted (cf. other JIRA reports) quite some ago that the API defined in package o.a.c.math4.ml.clustering could be improved.
Interest in this code has been recently renewed (cf. this thread on the "dev" ML).
This report will collect specific refactoring tasks.
Linked reports should serve as a guide towards a flexible API and efficient implementations.
Attachments
Issue Links
- is related to
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MATH-1516 Define an interface for ranking a list of clusters
- Resolved
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MATH-1520 A interface to implements various of clusters internal measurers
- Open
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MATH-1521 A interface to implements various of clusters external measurers
- Open
- relates to
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MATH-1171 clustering implementations have unnecessary overhead
- Open
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MATH-1367 DBSCAN Implementation does not count the seed point itself as part of its neighbors count
- Open
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MATH-1374 KMeansPlusPlusClusterer unable to converge having repeatable points in input dataset
- Open
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MATH-1315 MultiKMeansPlusPlusClusterer buggy for alternative evaluators
- Resolved
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MATH-1435 Implement cKMeans as a clustering algorithm
- Open
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MATH-1509 Implement the MiniBatchKMeansClusterer
- Open
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MATH-1519 Implement the Calinski-Harabasz clusters evaluator
- Resolved
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MATH-1235 Improve performance of DBSCAN clustering algorithm
- Open
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MATH-1330 KMeans clustering algorithm, doesn't support clustering of sparse input data.
- Open
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MATH-1378 KMeansPlusPlusClusterer optimize seeding procedure, by computing sum of squared distances outside the loop.
- Open
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MATH-1465 Increase the initial sampling speed of KMeansPlusPlusClusterer for large k
- Open
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MATH-1371 Provide accelerated kmeans++ implementation
- Resolved