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Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

[This FLIP proposal is a joint work between Dong Lin and Zhipeng Zhang]

Motivation

An important part of the Flink ML library infrastructure is the APIs to define, set and get parameters of machine learning stages (e.g. Transformer, Estimator, AlgoOperator). Currently Flink ML library provides these APIs through the public methods of WithParams (an interface), ParamInfo, ParamInfoFactory and Params (three classes). In this FLIP we propose to simplify the Flink ML library infrastructure by reducing the number of classes as well as the number of public methods on those classes, and still support all the expected use-cases.

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