Contains PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace. This course (formerly: Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (v18)) teaches you how to analyze text data using IBM SPSS Modeler Text Analytics. You will be introduced to the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model to perform churn analysis in telecommunications. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, and exclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to create resource tempates and Text Analysis packages to share with other projects and other users. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. Terms and Conditions: Ingram Micro – https://www.ingrammicrotraining.com/Terms-of-use.aspx; IBM – http://www.ibm.com/training/terms

Version:

v18.1.1

Audience:

Users of IBM SPSS Modeler responsible for building predictive models who want to leverage the full potential of classification models in IBM SPSS Modeler.

Objectives:

Detail:

eate categories from a pattern
? Use the visualization pane
? Create text link rules
? Use the Text Link Analysis node

Unit 10 – Clustering concepts
? Create Clusters
? Creating categories from cluster concepts
? Fine tuning Cluster Analysis settings

Unit 11 – Categorization techniques
? Describe approaches to categorization
? Use Frequency Based Categorization
? Use Text Analysis Packages to Categorize data
? Import pre-existing categories from a Microsoft Excel file
? Use Automated Categorization with Linguistic-based Techniques

Unit 12 – Creating categories
? Develop categorization strategy
? Fine turning the categories
? Importing pre-existing categories
? Creating a Text Analysis Package
? Assess category overlap
? Using a Text Analysis Package to categorize a new set of data
? Using Linguistic Categorization techniques to Creating Categories

Unit 13 – Managing Linguistic Resources
? Use the Template Editor
? Share Libraries
? Save resource templates
? Share Templates
? Describe local and public libraries
? Backup Resources
? Publishing libraries

Unit 14 – Using text mining models
? Explore text mining models
? Develop a model with quantitative and qualitative data
? Score new data

Appendix A – The process of text mining
? Explain the steps that are involved in performing a text mining project

Pre-Requisites:

? General computer literacy
? Prior completion of Introduction to IBM SPSS Modeler and Data Science (v18.1.1) is recommended.