Supervised Machine Learning Procedures Using SAS(R) Viya(R) in SAS(R) Studio

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Introduction to SAS Viya, Data Preparation, and Exploration

• Introduction to machine learning and SAS Viya.
• Supervised machine learning concepts.

Regression

• Introduction to regression.
• Categorical inputs.
• Interactions and polynomials.
• Selecting regression effects.
• Optimizing regression complexity.
• Interpreting regression models.
• Adjustments for oversampling.

Decision Tree

• Tree-structure models.
• Decision tree model essentials.
• Ensemble of trees.

Neural Network

• Introduction to neural networks.
• Neural network modeling essentials.
• Network architecture.
• Network learning.

Model Assessment

• Model assessment and comparison.

Support Vector Machine

• Introduction to support vector machines.
• Methods of solution.

Bayesian Networks

• Introduction.
• Network structures.

Factorization Machines

• Introduction to factorization machines.

Selected Topics