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IBM Data and AI Ideas Portal for Customers

This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (

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We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:

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Start by searching and reviewing ideas and requests to enhance a product or service. Take a look at ideas others have posted, and add a comment, vote, or subscribe to updates on them if they matter to you. If you can't find what you are looking for,

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Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

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Welcome to the IBM Ideas Portal ( - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal ( - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM. - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

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IBM Employees should enter Ideas at

Status Delivered
Created by Guest
Created on Aug 30, 2017

More control over model train/test/holdout data cuts

Given that model can be affected by the set of data used for training it, it would be nice to have better control over how the data is split up.

A fairly easy improvement is to allow the user to set a seed for controlling the splits, so you can replicate the split in the future.

A more complex change is to allow the user to specify how may different variations of the train/test split to generate and run models against, either combining the results into an ensemble or selecting the best of the variations as the "final" result.



  • Guest
    Oct 12, 2020

    Model Builder has been deprecated in favor of AutoAI. AutoAI supports specifying a custom split between the Training and Test dataset.