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https://issues.apache.org/jira/browse/MADLIB-1451?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1451:
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Priority: Minor (was: Major)
> DL: Improve output of predict
> -----------------------------
>
> Key: MADLIB-1451
> URL: https://issues.apache.org/jira/browse/MADLIB-1451
> Project: Apache MADlib
> Issue Type: Improvement
> Components: Deep Learning
> Reporter: Frank McQuillan
> Priority: Minor
> Fix For: v1.18.0
>
>
> **Story**
> Applies to
> https://madlib.apache.org/docs/latest/group__grp__keras__run__model__selection.html#keras_predict
> &
> https://madlib.apache.org/docs/latest/group__grp__keras.html#keras_predict
> &
> https://madlib.apache.org/docs/latest/group__grp__keras.html#keras_predict_byom
> Idea:
> Only want to run predict once and operate on the output table. You should
> not have to run predict over again to get a different format (e.g, top 1 vs.
> top 5), which would be inefficient. To do this we change the meaning of the
> param `pred_type` :
> {code}
> pred_type (optional)
> TEXT, default: 'all'. Type of output desired, where 'all' gives predictions
> for all classes and their associated
> probabilities. Alternatively, you can specify a filter for top n or minimum
> probability. For top n, use
> an INTEGER > 0 to indicate the top ranked probabilities to output. For
> minimum probability, specify
> a REAL value between 0.0 and 1.0 for the cutoff.
> {code}
> table output format
> {code}
> id | class | probability | rank
> ----+-------------------+---------------+----------
> 2 | Iris-setosa | 0.8704131 | 1
> 2 | Iris-versicolor | 0.09302262 | 2
> 2 | Iris-virginica | 0.036564212 | 3
> 9 | Iris-virginica | 0.7704131 | 1
> 9 | Iris-versicolor | 0.19302262 | 2
> 9 | Iris-setosa | 0.136564212 | 3
> etc.
> {code}
> **Open questions**
> 1) Will the above work OK with predict BYOM?
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