This blog is part of a series on SAS Visual Data Mining and Machine Learning (VDMML). If you're new to SAS VDMML and you want a brief overview of the features available, check out my last blog post! This blog will discuss types of missing data and how to use imputation
Some business models will segment the worth of their customers into categories that will often give different levels of service to the more “higher worth” customers. The metric most often used for that is called Customer Lifetime Value (CLV). CLV is simply a balance sheet look at the total cost spent versus the total revenue earned over a customer’s projected tenure or “life.”
Are you ready to get a jump start on the new year? If you’ve been wanting to brush up your SAS skills or learn something new, there’s no time like a new decade to start! SAS Press is releasing several new books in the upcoming months to help you stay
Did I trick you into seeing what this blog is about with its mysterious title? I am going to talk about how to use the FIND function to search text values. The FIND function searches for substrings in character values. For example, you might want to extract all email addresses
This article discusses how to use SAS to filter variables in a dataset based on the percentage of missing values or duplicate values. The missing value statistics can be implemented by either DATA step programming on your own or reusing the existing powerful PROC FREQ.
Parts 1 and 2 of this blog post discussed exploring and preparing your data using SASPy. To recap, Part 1 discussed how to explore data using the SASPy interface with Python. Part 2 continued with an explanation of how to prepare your data to use it with a machine-learning model.
Bringing the power of SAS to your Python scripts can be a game changer. An easy way to do that is by using SASPy, a Python interface to SAS allowing Python developers to use SAS® procedures within Python. However, not all SAS procedures are included in the SASPy library. So,
The DATA step remains a popular way to create and manipulate SAS data sets. Whether you are reshaping a data set entirely or simply assigning values to a new variable, there are numerous tips and tricks that you can use to save time and keystrokes.