Machine Learning Times
EXCLUSIVE HIGHLIGHTS
For Managing Business Uncertainty, Predictive AI Eclipses GenAI
  Originally published in Forbes The future is the ultimate...
AI Business Value Is Not an Oxymoron: How Predictive AI Delivers Real ROI for Enterprises
  Originally published in AI Realized Now “Shouldn’t a great...
How To Un-Botch Predictive AI: Business Metrics
  Originally published in Forbes Predictive AI offers tremendous potential...
2 More Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes Predictive AI and generative AI...
SHARE THIS:

10 years ago
Three Critical Definitions You Need Before Building Your First Predictive Model

 

Portions excerpted from Chapter 2 of his book Applied Predictive Analytics (Wiley 2014, http://amzn.com/1118727967)

Successful predictive modeling is more than identifying the right algorithms. And, even though 60-90% of our time is spend on data preparation before deploying the first predictive model built from a new data set, successful predictive modeling goes well beyond effective data cleaning and feature creation. I argue there, that most failed predictive modeling projects are on the path to failure before the first data set is even loaded because of these three steps that are frequently overlooked.

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.