Nandish Jayaram created MADLIB-1338:
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Summary: DL: Add support for reporting multiple metrics in
fit/evaluate
Key: MADLIB-1338
URL: https://issues.apache.org/jira/browse/MADLIB-1338
Project: Apache MADlib
Issue Type: New Feature
Components: Deep Learning
Reporter: Nandish Jayaram
Fix For: v1.16
The current {{madlib_keras.fit()}} code reports accuracy as the only metric,
along with loss value. But we could ask for multiple metrics in compile params
(for eg., {{metrics=['mae','accuracy']}}), then {{Keras.evaluate()}} would
return back {{loss}} (by default), {{mean_absolute_error}} and {{accuracy}}
(metrics).
This JIRA requests support to report all of these metrics in the output table.
Other requirements:
1. Output summary table must have a 2-D array to report {{metrics}}. The inner
dimension corresponds to all metrics values for the iteration at which it is
computed.
1. Output summary table must have the metrics' labels (eg.,
[mean_absolute_error, accuracy])
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