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:

2 years ago
A Refresher on Continuous Versus Discrete Input Variables

 How many times have I heard that the most critical element in predictive analytics is the data? Don’t misunderstand what I am saying. Method counts as well. But if there is a choice between better data or more methods, you can be sure that a data scientist would favor the richness of a data set. Data comes in different formats. But we are able to classify data into two types- continuous and discrete. Bottom line is, if a variable can assume any value between its minimum and maximum value, then it is called a continuous variable. Much of

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.