A continuation of Dr. Elder’s talk on the top ten data mining mistakes and how to avoid them. The Top Ten Mistakes are covered in chapter 20 of the Handbook of Statistical Analysis & Data Mining Applications. You can also view this talk as a PDF. (more…)
Too many people confuse reporting with analytics–and underinvest in making sure they are asking the right questions. Standard-issue reports about monthly employee turnover rates and average compensation per employee are important glances in the rearview mirror. But...
Surprisingly, latest KDnuggets Poll did not find a significant change in Text Analytics use over the past 2 years. While 66% make some use of text analytics, only 19% use it on the majority of their projects....
Building a data science team is difficult enough, but growing one without losing the team’s effectiveness is a major challenge. Here’s why overspecialization is the wrong approach to growth. You’ve built a great data science team,...
Dr. Elder gives his famous talk on the Top Ten Data Mining Mistakes. The Top Ten Mistakes are covered in chapter 20 of the Handbook of Statistical Analysis & Data Mining Applications. You can also view this...
Editor’s note: This article compares measures for model performance. Note that “accuracy” is a specific such measure, but that this article uses the word “accuracy” to generically refer to measures in general. In data mining, data scientists...
This speaker session is from Predictive Analytics World, September 30-October 1, 2013 in Boston, MA: (more…)
This speaker session is from Predictive Analytics World, September 30-October 1, 2013 in Boston, MA: (more…)
This speaker session is from Predictive Analytics World, September 30-October 1, 2013 in Boston, MA: (more…)
This speaker session is from Predictive Analytics World, September 30-October 1, 2013 in Boston, MA: (more…)
