Decision trees are one of the top machine learning algorithms used by data scientists. Decision trees use supervised learning to classify problems. Even if you are not a data scientist, chances are you can interpret the visual output from a decision tree.
The outbound marketing landscape, especially in the retail industry, is a challenging one. Customers are receiving multiple communications from multiple businesses, and for marketers it’s sometimes hard to understand which activity is driving results. Many retailers have a complex multichannel strategy of internet, email, direct mail, telemarketing, and catalogues. These
Marketers have used segmentation as a technique to target customers for communications, products, and services since the introduction of customer relationship management (i.e., CRM) and database marketing. Within the context of segmentation, there are a variety of applications, ranging from consumer demographics, geography, behavior, psychographics, events and cultural backgrounds. Over time, segmentation has proven its value,
This week's SAS tip is from Barry de Ville and Padraic Neville's new book Decision Trees for Analytics Using SAS Enterprise Miner. Filled with a multitude of examples and figures, this comprehensive book has received strong early user reviews. I hope that you'll also find this week's excerpt helpful in your
We’ve just published Decision Trees for Analytics Using SAS Enterprise Miner by Barry de Ville and Padraic Neville. Filled with many figures and examples, this comprehensive book has garnered strong early user reviews. We invited the authors to share a few words about their new book. Neville had this to
