Workshop

The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

Intended Audience: Interested in the true nuts and bolts

Knowledge Level: Familiar with the basics of predictive modeling

Instructor:
Dr. John F. Elder

John F. Elder, Ph.D., CEO and Founder, Elder Research, Inc.

Day: February 20, 2009

Time: 9.00am – 4.30pm

Predictive analytics has proven capable of enormous returns across industries – but, with so many core methods for predictive modeling, there are some tough questions that need answering:

How do you pick the right one to deliver the greatest impact for your business, as applied over your data?

What are the best practices along the way?

And how do you avoid the most treacherous pitfalls?

This one-day session surveys standard and advanced methods for predictive modeling.
Dr. Elder will describe the key inner workings of leading algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to pick the method and tool best suited to each predictive analytics project. Methods covered include classical regression, decision trees, neural networks, ensemble methods, uplift modeling and more.

The key to successfully leveraging these methods is to avoid “worst practices”. It's all too easy to go too far in one's analysis and “torture the data until it confesses” or otherwise doom predictive models to fail where they really matter: on new situations.
Dr. Elder will share his (often humorous) stories from real-world applications, highlighting the Top 10 common, but deadly, mistakes. Come learn how to avoid these pitfalls by laughing (or gasping) at stories of barely averted disaster.

If you'd like to become a practitioner of predictive analytics – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!