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https://issues.apache.org/jira/browse/MADLIB-1335?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan closed MADLIB-1335.
-----------------------------------
Resolution: Fixed
> 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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