SAS: Prepare Data Working with Variables Sort variables Perform variable imputation Perform supervised and unsupervised variable selection Clean the Data Remove trailing blanks Manage missing values Transform Data Transpose data Perform binning Cluster the Data Perform clustering with the K-means algorithm Perform clustering with the K-means nearest neighbor algorithm Perform clustering with the Gaussian mixture model Perform hierarchical clustering Save and Export the Data Save to an external database Export to an external data source Use Cases: Machine Learning Perform variable clustering and graphical modeling Perform binary classification on sparse input data sets Implement t-distributed stochastic neighbor embedding eimension reduction to visualize high-dimensional data Use Cases: Computer Vision Search for a matching image in a large collection of images SAS Courses Statistics You Need to Know for Machine Learning Last updated: April 20, 2026
