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From "Aleksey Zinoviev (Jira)" <j...@apache.org>
Subject [jira] [Updated] (IGNITE-7328) Improve Labeled Dataset loading from txt file
Date Wed, 25 Sep 2019 09:16:00 GMT

     [ https://issues.apache.org/jira/browse/IGNITE-7328?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Aleksey Zinoviev updated IGNITE-7328:
-------------------------------------
    Affects Version/s: 3.0

> Improve Labeled Dataset loading from txt file
> ---------------------------------------------
>
>                 Key: IGNITE-7328
>                 URL: https://issues.apache.org/jira/browse/IGNITE-7328
>             Project: Ignite
>          Issue Type: New Feature
>          Components: ml
>    Affects Versions: 3.0
>            Reporter: Aleksey Zinoviev
>            Assignee: Aleksey Zinoviev
>            Priority: Trivial
>
> 1. Wouldn't it be better to parse rows in-place (not to save them as strings at first)?
In current implementation we will be needed to keep a dataset in memory twice and it might
be a problem for big datasets.
> 2. What about the case when a dataset contains not only a numerical data? Do we consider
this case or for such purposes some other "DatasetLoader" will be used?
> 3. Just an idea, in case we don't want to fall on bad data (99% of cases) would be great
to understand the quality of loaded dataset such as number of missed rows/values.
> 4. Does a situation when a row doesn't contain required number of columns should be considered
as "bad data" and don't break parsing with IndexOutOfBoundException?



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