Network Analysis and Network Optimization in SAS® Viya®
This course provides a set of algorithms to perform both network analysis and network optimization. Practical demonstrations and exercises emphasize the theory, and business case studies illustrate the possible outcomes from such techniques. Hands-on activities are based on the NETWORK and OPTNETWORK procedures in SAS Viya.
Network analysis includes graph theory algorithms that can augment data mining and machine learning. In many practical applications, pairwise interaction between the entities of interest in the model often plays an important role. Network analysis goes beyond traditional clustering and predictive models to identify patterns in business data, including entities’ behavior based on their relationships. Network analysis can be employed to avoid churn, diffuse products and services, detect fraud and abuse, identify anomalies, and many other applications, in a wide range of industries such as communications and media, banking, insurance, retail, utilities, and travel and transportation.
Network optimization includes graph theory algorithms that can augment more generic mathematical optimization approaches. Many practical applications of optimization depend on an underlying network. Networks also appear explicitly and implicitly in many other application contexts. Networks are often constructed from certain natural co-occurrence types of relationships, such as relationships among researchers who coauthor articles, actors who appear in the same movie, words or topics that occur in the same document, items that appear together in a shopping basket, terrorism suspects who travel together or are seen in the same location, and so on. In these types of relationships, the strength or frequency of interaction is modeled as weights on the links of the resulting network.Lernen Sie, wie Sie / Learn how to
Zielgruppe / Who should attendData scientists, business analysts, statisticians, mathematicians, network engineers, computer scientists, data analysts, data scientists, quantitative analysts, data miners, marketing analysts, risk and fraud analysts, analytical model developers, and marketing modelers in all industries, including but not limited to communications and entertainment, banking and finance, insurance and retailers
To complete exercises with classroom software, you should have at least a beginner-level background in statistics and mathematics and be minimally familiar with SAS programming.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet: SAS Viya Software
Concepts in Network Analysis