Analyzing Data

Use Cases

SAS

Perform Correlation Analysis on Customer Trends Using a Regression Forest Model

Identify Factors Impacting the Student Dropout Rate Using the GRADBOOST Procedure

Identify Factors Impacting the Student Dropout Rate Using the SVMACHINE Procedure

Use Principal Component Analysis (PCA) to Analyze Breast Cancer Data

Python

Perform Correlation Analysis on Customer Trends Using a Regression Forest Model

Predict Whether a Client Will Subscribe to an Offering as a Result of a Marketing Campaign Using Gradient Boosting

Create a Support Vector Machine (SVM) Model to Predict Bonuses

Determine Whether a Mushroom Sample Is Poisonous Using Principal Component Analysis (PCA)

Examples by Language

GitHub: SAS Viya Workbench Examples (Python)

GitHub: SAS Viya Workbench Examples (SAS)

Advanced Analytics Tasks

This page highlights some frequently used tasks for analyzing data. For documentation of all SAS procedures, see SAS Viya Workbench Procedures by Name and Capability.

Machine Learning Procedures

Score New Data Using the ASTORE Procedure

Implement the K-Nearest Neighbor Search Algorithm Using the FASTKNN Procedure

Perform Gaussian Process Classification Using the GPCLASS Procedure

Perform Gaussian Process Regression on Large Data Sets Using the GPREG Procedure

Perform Variable Clustering and Graphical Modeling Using the GVARCLUS Procedure

Perform Binary Classification on Sparse Input Data Sets Using the SPARSEML Procedure

Implement Dimension Reduction to Visualize High-Dimensional Data Using the TSNE Procedure

Computer Vision Procedures

Convert a Wide Table to an Image Table Using the CONDENSEIMAGES Procedure

Display Images from an Image Binaries Input Table Using the DISPLAYIMAGES Procedure

Produce an Output Table from an Image Input Table Using the FLATTENIMAGES Procedure

Read Data from Files That Comply with the Digital Imaging and Communications in Medicine (DICOM) Standard Using the LOADDICOMDATA Procedure

Load Images and Associated Metadata into a Data Set Using the LOADIMAGES Procedure

Search for a Matching Image in a Large Collection of Images Using the MATCHIMAGES Procedure

Specify Image-Processing Algorithms to Apply to Images in an Input Table Using the PROCESSIMAGES Procedure

Write Images and Associated Metadata from a SAS Table to Disk Using the SAVEIMAGES Procedure

Statistics Procedures

Assess and Compare Supervised Learning Models Using the ASSESS Procedure

Perform Binning with a Specified Method Using the BINNING Procedure

Determine a Variable's Cardinality Using the CARDINALITY Procedure

Fit and Perform Model Selection of Generalized Linear Models (GLMs) Using the GENSELECT Procedure

Perform Sampling Using the PARTITION Procedure

Build Tree-Based Statistical Models for Classification and Regression Using the TREESPLIT Procedure

Perform Variable Imputation Using the VARIMPUTE Procedure

Perform Supervised and Unsupervised Variable Selection Using the VARREDUCE Procedure

Last updated: September 20, 2024