Description: Introducion to a class of methods known as data mining that assists managers in recognizing patterns and making intelligent use of massive amounts of electronic data collected via the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Topics selected from: subset selection in regression; collaborative filtering; tree-structured classification and regression; cluster analysis; and neural network methods. Examples of successful applications in areas such as credit ratings, fraud detection, database marketing, customer relationship management, investments, and logistics are covered. Hands-on experimentation with data-mining and statistics software.
Course #: 15.062
Professor(s) who recently taught this course:
Dimitris Bertsimas
Nitin Patel
Roy Welsch