Fan Hong created FLINK-30734:
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Summary: KBinsDiscretizer handles Double.NaN incorrectly
Key: FLINK-30734
URL: https://issues.apache.org/jira/browse/FLINK-30734
Project: Flink
Issue Type: Bug
Components: Library / Machine Learning
Reporter: Fan Hong
When the training data contains Double.NaN values and the strategy is set to
"quantile", the generated model data has Double.NaN as the right edge of the
largest bin.
My expected behavior is to ignore Double.NaN values when training, and to
support skip/error/keep strategy when transforming with generated
KBinsDiscretizerModel.
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