Segmentation techniques
Aims
The course covers the theory and application aspects of clustering techniques available in SAS. Topics include data preparation for clustering, main components analysis and factorial analysis for the reduction of input dimensions, variable clustering, the k-nearest-neighbor methods, k-average method, hierarchical clustering techniques and fuzzy dustering.
Who should attend
Statistical analysts, data mining experts, business users; the topics covered will mainly make reference to the area of marketing databases.
Prerequisites
Basic experience in the use of the SAS language and fundamentals in statistics. Basic experience in data analysis is recommended.
Course outline
Database creation
- Defining phenomenon to be analysed
- Identifying data sources
- Customer Table Design and Construction
- Features analysis (missing, outlier, etc.)
Clustering Analysis
- Main component analysis
- Factorial analysis
- Conducting a cluster analysis
- Hierarchical clusterisation methods
- K-average method
- Kohonen maps for group analysis
- Group profiling
Duration
The duration of the course is 3 days.