This course describes the functionality of SAS Text Miner software, which is a separately licensed component that is available for SAS Enterprise Miner. In this course, you learn to use SAS Text Miner to uncover underlying themes or concepts contained in large document collections, automatically group documents into topical clusters, classify documents into predefined categories, and integrate text data with structured data to enrich predictive modeling endeavors.
Text Analytics Using SAS(R) Text Miner
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
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
- 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.
Introduction to SAS Enterprise Miner and SAS Text Miner
- data mining and text mining
- working with data sources
- using SAS Enterprise Miner and SAS Text Miner
Overview of Text Analytics
- using the Text Import node, adding a target variable, and comparing models
- a forensic linguistics application
- information retrieval
Algorithmic and Methodological Considerations in Text Mining
- methods for parsing and quantifying text
- dimension reduction with SVD
Additional Ideas and Nodes
- some predictive modeling details
- Text Rule Builder node
- High Performance (HP) Text Miner node
This is a QA approved partner course
Face-to-face learning in the comfort of our quality nationwide centres, with free refreshments and Wi-Fi.
Find dates and prices
Online booking is currently not available for this course, to find out more please call us on 01753 898320 or email us at email@example.com to discuss how we can help.
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