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https://issues.apache.org/jira/browse/MADLIB-1335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16854967#comment-16854967
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Ekta Khanna commented on MADLIB-1335:
-------------------------------------

Merged as part of PR: [https://github.com/apache/madlib/pull/388]

> Add new param metrics_compute_frequency to madlib_keras_fit()
> -------------------------------------------------------------
>
>                 Key: MADLIB-1335
>                 URL: https://issues.apache.org/jira/browse/MADLIB-1335
>             Project: Apache MADlib
>          Issue Type: New Feature
>          Components: Deep Learning
>            Reporter: Ekta Khanna
>            Priority: Major
>             Fix For: v1.16
>
>
> JIRA: https://issues.apache.org/jira/browse/MADLIB-1335
> Context
> Getting per iteration loss and other metrics for training and validation data 
> sets can be expensive.  This parameter is intended to give control to user on 
> how often to do this computation.
> Story
> As a data scientist, I want to specify how often to calculate loss and other 
> metrics for training and validation data (if provided), i.e, every n 
> iterations
> Interface
> {code}
> madlib_keras_fit(
>     source_table            VARCHAR,
>     model                   VARCHAR,
>     dependent_varname       VARCHAR,
>     independent_varname     VARCHAR,
>     model_arch_table        VARCHAR,
>     model_arch_id           INTEGER,
>     compile_params          VARCHAR,
>     fit_params              VARCHAR,
>     num_iterations          INTEGER,
>     use_gpu                 BOOLEAN,
>     validation_table        VARCHAR,
>     metrics_compute_frequency      INTEGER   <-------- NEW OPTIONAL PARAM
>     name                    VARCHAR,
>     description             VARCHAR
> {code} 
> where `metrics_compute_frequency` is an optional parameter that means:
> {code}
> NULL  - calculate loss and metrics only on final model after last iteration 
> (default)
> n - calculate loss metrics every n-th iteration and on final model after last 
> iteration
> {code}
> and `metrics_compute_frequency must be >=1 and <=num_iterations`
> Acceptance
> 1) Set `num_iterations = 12` and leave ` metrics_compute_frequency` as 
> default and get 1 loss and metrics value at end after 12 iterations
> 2) Set `num_iterations = 12` and set `metrics_compute_frequency = 5` and get 
> loss and metrics after 5th and 10th iterations and at end after 12 iterations
> 3) Set `metrics_compute_frequency = 0` and get an error
> 4) Set `metrics_compute_frequency = num_iterations+1` and get an error
> 5) Test with different metrics:  from https://keras.io/metrics/ try 'mae' , 
> 'acc' etc.
> Reference
> [1] https://keras.io/metrics/



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