[jira] [Resolved] (MADLIB-1451) DL: Improve output of predict

["Frank McQuillan (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MADLIB-1451?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Frank McQuillan resolved MADLIB-1451.
-------------------------------------
    Resolution: Fixed

https://github.com/apache/madlib/pull/514

> 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
>            Assignee: Orhan Kislal
>            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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