Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
SHARE THIS:

9 years ago
It is a Mistake to…. Answer Every Inquiry

 (Part 9 (of 11) of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) I’m tempted to start with a kind of query that experience teaches some of us not to answer, like “Does this data make me look fat?” But that actually misleads about the point I’m trying to make. Data Scientists (and their models) should answer all queries as truthfully as the evidence allows, regardless of how happy or unhappy that makes the questioner. What I am arguing here is we shouldn’t answer when our opinion is unqualified;

This content is restricted to site members. If you are an existing user, please log in on the right (desktop) or below (mobile). If not, register today and gain free access to original content and industry news. See the details here.

Comments are closed.