Add query based input into interfaces #25
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| * @param modelId the trained model id | ||
| * @param listener a listener to be notified of the result | ||
| */ | ||
| default void predict(String algorithm, List<MLParameter> parameters, DataFrame inputData, String modelId, ActionListener<DataFrame> listener) { |
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Do we have a supported algorithm list? How about add the list or add the doc link in java doc , so the client can know the exact algorithm name they should use?
Another option is to add enum for support algorithm. So user can just use code like this SupportedMLAlgorithm.KMEANS easily without worrying about wrong algorithm name (kMeans, kmean, or k_means?), but maybe the list will be too long.
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The built-in algorithms candidates are available in the first release For these, we plan to have official page to share the details of each algorithm. We can add that link into the java doc. One issue is created to track this change. #26
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For the algorithm enum, we can have an enum for built-in algorithms, but for interface, String will be still used to support custom algorithms built by customers.
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Oh, it's great that we will support custom algorithms. Then it make sense to use string here. Maybe another interface with enum as input is more friendly for users who use built-in algorithms.
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Thanks for the comment. Created issue to track this change. #28 Personally I prefer not providing enum interface, since it will increase some cognitive load to customers. Adding this enum in the javadoc of the interfaces should be good enough. But still open to change this.
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Add query based input into interfaces
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