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  1. Flink
  2. FLINK-1723

Add cross validation for model evaluation

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    Description

      Cross validation [1] is a standard tool to estimate the test error for a model. As such it is a crucial tool for every machine learning library.

      The cross validation should work with arbitrary Estimators and error metrics. A first cross validation strategy it should support is the k-fold cross validation.

      Resources:
      [1] http://en.wikipedia.org/wiki/Cross-validation

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          is required by

          New Feature - A new feature of the product, which has yet to be developed. FLINK-2258 Add hyperparameter optimization to FlinkML

          • Major - Major loss of function.
          • Closed

          New Feature - A new feature of the product, which has yet to be developed. FLINK-2260 Have a complete model evaluation and selection framework for FlinkML

          • Major - Major loss of function.
          • Closed
          requires

          New Feature - A new feature of the product, which has yet to be developed. FLINK-2157 Create evaluation framework for ML library

          • Major - Major loss of function.
          • Closed
          links to

          Web Link GitHub Pull Request #891

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              tvas Theodore Vasiloudis
              trohrmann Till Rohrmann
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