The starting point for your SAS® and Viya™ projects
Discover technical articles from the community
Snippets & Tutorials
FAQ & Help
Business Use Cases
Full Catalog & Examples
Preparation Scripts
SAS & Python Integration
News, tech watch and site updates
Participate in the life of the site
The bnet action from the Bayesian Net Classifier action set uses Bayesian networ...
Generates DATA step scoring code from a gradient boosting tree model....
The forestScore action scores an input table using a previously trained forest m...
The caslibInfo action shows information about caslibs.
The minCut action can produce two main output tables: 'outCutSets' to store the links that form the minimum cut sets, and 'outPartitions' to store the minimum cut partitions of the nodes.
specifies the when standardizedLabels is specified, vertex2Number specifies the second vertex that Analytics of Vertices are to be performed upon. Results will be put into the vertices5= and edges5= tables. Alias: vertexNumber2. Minimum value: 0.
The 'table' parameter is required to specify the input data table. It identifies the table that contains the data to be analyzed.
The process standard deviation is estimated using the method specified in the `sMethod` parameter. You can choose from three methods: 'RMSDF' (a weighted root mean square estimate), 'SMVLUE' (a minimum variance linear unbiased estimate based on subgroup standard deviations), or 'SNOWEIGHT' (an unweighted estimate based on subgroup standard deviations). The default method is 'SNOWEIGHT'.