Version 4.2 of the Predictive Model Markup Language (PMML), which aims to make it easier to develop predictive analytics apps, is now available. The Data Mining Group, a vendor-led consortium of companies and organizations developing standards for statistical and data mining models, has released v 4.2 of the Predictive Model Markup Language (PMML), an XML
Before companies can profit from big data, they often must deal with bad data. There may indeed be gold in the mountains of information that firms collect today, but there also are stores of contaminated or “noisy”...
Machine learning technology, which is defined in this ProgrammableWeb article, is starting to become a common component in many types of technology platforms. Machine learning has led to the advent of predictive analytics, which has been rapidly...
It’s not every day that Brady gets sent packing, Manning sends potential travelers scrambling to the midwest and a Stanford grad makes news for freaking out on reporter Erin Andrews but that’s exactly what happened on Sunday....
The majority of consumer packaged goods (CPG) companies are failing to place analytics at the heart of their decision-making process, limiting their ability to improve the customer experience and gain business advantage, a study by Accenture has...
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....
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...