Description
Summary: Create a class hierarchy for learning algorithms and the models those algorithms produce.
This is a super-task of several sub-tasks (but JIRA does not allow subtasks of subtasks). See the "requires" links below for subtasks.
Goals:
- give intuitive structure to API, both for developers and for generated documentation
- support meta-algorithms (e.g., boosting)
- support generic functionality (e.g., evaluation)
- reduce code duplication across classes
Attachments
Issue Links
- is depended upon by
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SPARK-4591 Algorithm/model parity for spark.ml (Scala)
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- Resolved
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- is related to
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SPARK-3507 Create RegressionLearner trait and make some currect code implement it
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- Closed
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SPARK-3251 Clarify learning interfaces
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- Resolved
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- relates to
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SPARK-10817 ML abstraction umbrella
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- Resolved
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- requires
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SPARK-4789 Standardize ML Prediction APIs
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- Resolved
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SPARK-5995 Make ML Prediction Developer APIs public
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- Resolved
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- links to