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 (https://ideas.ibm.com).


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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,

  1. Post an idea

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  3. Get feedback from the IBM team to refine your idea


Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal (https://ideas.ibm.com) - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM.

ideasibm@us.ibm.com - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Employees should enter Ideas at https://ideas.ibm.com


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Status Not under consideration
Workspace watsonx Assistant
Created by Guest
Created on May 1, 2018

RELATED IDEAS

Rename the "confidence" value to "score"

In mathematics, the standard way to refer to the numeric output representative of certainty of a classification algorithm is as a "score."  The name of this in the json structure returned by Watson Assistant currently is "confidence".  However, this has caused confusion with our clients. (https://en.wikipedia.org/wiki/Statistical_classification vs https://www.merriam-webster.com/dictionary/confidence)


Consider the following scenario:  the IBM expert services team numerically calculates the best threshold to hand off from one Assistant's domain to another domain.  That threshold, currently called "confidence" is 0.2.  The client doesn't understand why anything with a "confidence" above 0.2 would be considered a good response.  We have been trained as a society to call things on a 0-1 scale labeled as "confidence", anything below 0.6 would be "failing".  However, this is not the correct interpretation of this number.  In fact, a machine learning score is only be interpreted in terms of its relation on how it performs on a set of data.  In this particular example, a "confidence" ("score") of 0.2 resulted in a system that was 75% accurate. 
This suggestion comes from feedback directly from the customer during our GEICO virtual agent development.

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