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Welcome to college, freshmen. Now look at the neighbor on your left, and the...
While other analytics methods analyze past events, monitor real-time ones, or provide operational reporting,...
Industry leader and author Dean Abbott will be presenting at Predictive Analytics World Boston (Oct 5 – 9) on “Data Preparation from the Trenches: 4 Approaches to Deriving Attributes.” Abbott will also run two post-conference full-day training workshops, “Advanced Methods Hands-on: Predictive Modeling Techniques” (where his book Applied Predictive Analytics will be given to attendees), […]
In my last two posts I described why overfitting predictive models is dangerous beyond the most obvious problem, namely that accuracy on new data is lower than expected. In the next few posts, I’ll describe how to recognized that overfitting may be occurring, and some common approaches to remove or mitigate the effects of overfitting. […]
Presented by: Pasha Roberts, Chief Scientist, Talent Analytics, Corp. Watch Webinar. Pasha Roberts, Chief Scientist at Talent Analytics, Corp., discusses Talent Analytics’ first step when using a predictive analytics approach for solving employee attrition challenges. Severe employee attrition can be a thing of the past. It need not be the “cost of doing business”. Talent […]
(Part 5 of 11 of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) Inducing models from data has the virtue of looking at the data afresh, not constrained by old hypotheses. But, while “letting the data speak”, don’t tune out received wisdom. Experience has taught this […]
Building predictive analytics solutions is very much in-vogue for most organizations today. Historically, practitioners needed to educate businesses on the value of data mining and predictive analytics. Now, the concept and value of predictive analytics is widely accepted by most businesses. Demonstrating the value of solutions thru various techniques and approaches represents the exciting component […]
(adapted from Chapter 13 of the Handbook of Statistical Analysis and Data Mining Applications) After a first pass of training and evaluating a model, you may find you need to improve its results. Here is a checklist of ten practical actions that I’ve found usually help: Transform real-valued inputs to be approximately Normal in […]
In the analytics space, it is quite common for many organizations to have a team of data miners who are now referred to as data scientists and a team of business users who are often referred to as value architects. It has been a common practice ever since the first direct marketing models were produced […]