[ https://issues.apache.org/jira/browse/MADLIB-1338?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Orhan Kislal updated MADLIB-1338: --------------------------------- Description: The current {{madlib_keras.fit()}} code reports accuracy as the only metric, along with loss value. But we could ask for different metrics in compile params ({{mae, binary_accuracy}} etc.), then {{Keras.evaluate()}} would return back {{loss}} (by default) and {{mean_absolute_error}} or {{binary_accuracy}} (metrics). This JIRA requests support to report all of these metrics in the output table. Other requirements: Output summary table must have the metrics' labels (instead of just accuracy) Remove loss/accuracy computation from fit_transition. was: 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]) Summary: DL: Add support for reporting various metrics in fit/evaluate (was: DL: Add support for reporting multiple metrics in fit/evaluate) > DL: Add support for reporting various 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 > Priority: Major > 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 different metrics in compile > params ({{mae, binary_accuracy}} etc.), then {{Keras.evaluate()}} would > return back {{loss}} (by default) and {{mean_absolute_error}} or > {{binary_accuracy}} (metrics). > This JIRA requests support to report all of these metrics in the output table. > Other requirements: > Output summary table must have the metrics' labels (instead of just accuracy) > Remove loss/accuracy computation from fit_transition. -- This message was sent by Atlassian JIRA (v7.6.3#76005)