Machine Learning Times
EXCLUSIVE HIGHLIGHTS
How To Overcome The Confidence-Killer That Destroys Most Predictive AI Projects
  Originally published in Forbes When Henry Castellanos first presented...
You Must Address These 4 Concerns To Deploy Predictive AI
 Originally published in Forbes Most predictive AI projects fail to launch into production. The...
Hybrid AI: Industry Event Signals Emerging Hot Trend
 Originally published in Forbes After decades chairing and keynoting myriad...
Predictive AI Thrives, Despite GenAI Stealing The Spotlight
 Originally published in Forbes Generative AI and predictive AI ought...
SHARE THIS:

By: Dean Abbott, President, Abbott Analytics 

 The Cross Industry Standard Process for Data Mining (CRISP-DM) is the leading published methodology for Data Mining (DM), and by extension, Predictive Analytics (PA). I use it routinely as I lead PA projects and when I teach appiled DM and PA courses. It was the subject of three KD-Nuggets polls, in 2002, 2004, and 2007) and nearly half of the responders stated they used it as the main methodology for DM (http://www.kdnuggets.com/polls/2007/data_mining_methodology.htm). There are six stages in the CRISP-DM process, including Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment. There are many excellent books describing five

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.