September 30, 2015 | 12:00pm - 2:00pm
Issue of Classification Versus Precision in Comparing Classification Models
We contrast classification and precision rates as tools for model diagnosis and comparison for binary target models. These types of models are of constant use in the database marketing area, banking, telecommunications and clinical research, among others. We review advantages and disadvantages in their respective usage, and relate them to the Bayesian Theorem. In tandem, we review their connection to ROC and Lift curves.
Independent Statistical Research Consultant
Leonardo Auslender is a statistician (and economist) with more than 25 years of business experience and SAS expertise. His area of expertise is in the area of Giga-Data Analysis and Methods, and has written papers and given lectures on Variable Selection, Missing Value Imputation, Tree Regression, Support Vector Machines, Market-Basket Analysis, Data Base Marketing, CRM, GDP and (Relative Price) Inflation studies, Expectation Formations, Productivity and Technology effects in the economy. He was a lecturer of Finance and Macroeconomics at Rutgers University. He presented two seminars on Market Basket Analysis in New York City (Informs and Amcis), a two-day seminar at the NYC Direct Marketing Association on Variable and Feature Selection in November, 2004, on Colinearity and Variable Selection at the December 2005 SCMA meeting in Auburn, Alabama, on Modeling issues at the SAS M2007 and M2008 Data Mining Conferences and at the Informs in NYC.