Learn how to:
- Process textual data and show how it can be used in predictive modeling and exploratory analysis
- Convert unstructured character data into structured numeric data
- Explore words and phrases in a document collection
- Cluster documents into homogeneous subgroups
- Find documents most closely associated with a word or phrase
- Find words or phrases most closely associated with a document
- Identify topics in a document collection
- Classify documents based on derived or user-supplied topic definitions
- Extract a subset of documents with term-based and string-based query filters
- Use textual data to improve predictive models.
Who should attend: Statisticians, business analysts, and market researchers who incorporate free-format textual information in their analyses; managers of large document collections who must organize and select documents using data mining; students of data mining who want to learn about text mining.
Before attending this course, you should have experience using SAS Enterprise Miner to do pattern discovery and predictive modeling, or you should complete the Applied Analytics Using SAS Enterprise Miner course.
A three-day version of this course contains the appropriate introductory material for using SAS Enterprise Miner. For the three-day course, you should also
- Be acquainted with Microsoft Windows and Windows-based software
- Have at least an introductory-level familiarity with basic statistics and regression modeling.
Previous SAS software experience, especially SAS Enterprise Miner, is helpful but not required. This course uses SAS Text Miner 13.1 and SAS Enterprise Miner 13.1.
This course addresses SAS Text Miner, SAS Text Analytics software.