[jira] [Created] (MADLIB-1338) DL: Add support for reporting multiple metrics in fit/evaluate

["Nandish Jayaram (JIRA)" <ji...@apache.org>]

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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