Details
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Improvement
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Status: Resolved
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Major
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Resolution: Fixed
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None
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None
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None
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None
Description
In order to be able to implement Stochastic Gradient Descent and a number of other machine learning algorithms we need to have a way to take a random sample from a Dataset.
We need to be able to sample with or without replacement from the Dataset, choose the relative or exact size of the sample, set a seed for reproducibility, and support sampling within iterations.
Attachments
Issue Links
- blocks
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FLINK-1807 Stochastic gradient descent optimizer for ML library
- Closed
- contains
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FLINK-1742 Sample data points for MultipleLinearRegression to support proper SGD
- Closed
- is depended upon by
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FLINK-2533 Gap based random sample optimization
- Resolved
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FLINK-2535 Fixed size sample algorithm optimization
- Closed
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FLINK-3783 Support weighted random sampling with reservoir
- Closed
- is related to
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FLINK-2549 Add topK operator for DataSet
- Reopened
- relates to
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FLINK-2396 Review the datasets of dynamic path and static path in iteration.
- Open