Everyone is welcome to attend. There is no fee for these seminars, but space is limited so pre-registration is essential.
Title: Do Numbers Lie? A Data Mining Practitioners Viewpoint
In many data mining exercises, we see information that appears on the surface to demonstrate a particular conclusion. But closer examination of the data reveals that these results are indeed misleading. In this session, we will examine this notion of misleading results in three areas:
Statistical issues such as multicollinearity and outliers can impact results dramatically. We will first outline how these statistical issues can provide misleading results. At the same time, we will demonstrate how the data mining practitioner overcomes these issues through data analysis approaches that provide both more meaningful and non-misleading results to the business community.
Overstating of Results
From a business standpoint, we will also look at results that appear to be too good to be true. In other words, there appears to be some overstating of results within a given data mining solution. Initially, we will discuss how to identify these situations. Secondly, we will outline what causes this overstatement of results and detail our approach on how we would overcome this predicament.
Another topic for discussion is overfitting of results. This is particularly the case when building predictive models. In this section of the seminar, we will define what overfitting is and why it is becoming more relevant for understanding by the business community. Once again, analytical approaches will be discussed in terms of how to best handle this issue.
About the Speaker: Richard Boire
Richard Boire's experience in database marketing and data mining dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics. Immediately after, he joined Reader's Digest where he developed segmentation and modeling routines for all direct marketing programs.
Richard's progressive career path led him to American Express, where he pioneered predictive modelling technology for all direct marketing programs. He was quickly promoted to senior manager, responsible for credit risk and market behaviour segmentation. As a result of this expanded role, he pioneered the development of models which targeted the acquisition of new customers based on return on investment.
With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler group , an organization which offers analytical and database services to companies seeking solutions to their existing data mining or database marketing challenges.
Richard is a recognized authority on data mining and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. He gives seminars on segmentation and data mining for such organizations as Canadian Marketing Association (CMA), Direct Marketing News,Direct Marketing Association Toronto and AARM. His articles have appeared in Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics and database marketing at Concordia University, Vanier College in Montreal, and Humber College in Toronto and is currently a part-time lecturer at George Brown in Toronto. Richard is currently Vice Chair at the CMA's Database and Technology Committee where he has chaired sub-committees responsible for both the 2000 Database and Technology Seminar as well as the 2002 Database and Technology Seminar and is currently chairing the Customer Profitability Conference which is being held on Nov.17/2005. He co-authored a white paper entitled Best Practices in Data Mining and is currently working on another paper entitled Best Practices in Customer Profitability.
If you plan to attend this seminar, please RSVP to Alison Burnham by e-mail. Please contact Alison if you want more information about the SORA Financial Statistics/Marketing Seminars.
Chair, SORA Committee for Financial Statistics & Marketing
Co-sponsorship for these seminars is provided by SAS, Scotiabank, RBC Financial Group and Trans Union of Canada.