Everyone knows that SAS has been helping programmers and coders build complex machine learning models and solve complex business problems for many years, but did you know that you can also now build machines learning models without a single line of code using SAS Viya? SAS has been helping programmers […]
The value of a low-code/no-code approach to building machine learning models was published on SAS Users.
What is automated prediction?
Automated prediction, in less than a minute, runs several analytic models (such as decision trees, gradient boosting, and logistic and linear regression) on a specific variable of your choice. Most of the remaining variables in your dataset are automatically analyzed as factors that might influence your specified variable. They are called underlying factors. SAS then chooses the one model (champion model) that most accurately predicts your target variable. The model prediction and the underlying factors are then displayed. You can adjust the values of the underlying factors to determine how the model prediction changes with each adjustment.
How SAS Visual Analytics’ automated prediction takes customer care to the next level was published on SAS Users.
Let’s learn how to prompt for a date range in a SAS Visual Analytics report using control objects such as sliders, drop-down lists, and text input.
How to prompt for a date range in a SAS Visual Analytics Report – Four Part Series was published on SAS Users.
Common filters are filters that can be shared between objects in your reports. Common filter benefits include 1) Easy to assign the same filter conditions to other report objects, 2) When you edit a common filter, it is updated everywhere that the common filter is used, and 3) A common filter is available for the entire report, across pages.
Using common filters in SAS Visual Analytics was published on SAS Users.
In this blog, I will show you how a Viya administrator can track and control resource usage of personal caslibs.
Viya administrators can now get personal with users’ Caslibs was published on SAS Users.
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.”
How to utilize Customer Lifetime Value with SAS Visual Analytics was published on SAS Users.
Introduced in the SAS Visual Analytics 8.4 release is the ability to control the layout position of these prompts. Using my example report, let’s change the placement of these prompts.
New control prompt placement option in SAS Visual Analytics was published on SAS Users.
Importing about 4,400 messages worth of data into SAS Visual Text Analytics to exploring it and create an information extraction model.
A data fairy tale: Which speakers are the best received at conferences? was published on SAS Users.