Table of Contents

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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Classifier Transformation Overview

Classifier Transformation Overview

The Classifier transformation is a passive transformation that analyzes input fields and identifies the type of information in each field. Use a Classifier transformation when input fields contain multiple text values.
When you configure the Classifier transformation, you select a classifier model and a classifier algorithm. A classifier model is a type of reference data object. A classifier algorithm is a set of rules that calculates the number of similar words in a string and the relative positions of the words. The transformation compares the algorithm analysis with the content of the classifier model. The transformation returns the model classification that identifies the dominant type of information in the string.
The Classifier transformation can analyze strings of significant length. For example, you can use the transformation to classify the contents of email messages, social media messages, and document text. You pass the contents of each document or message to a field in a data source column, and you connect the column to a Classifier transformation. In each case, you prepare the data source so that each field contains the complete contents of a document or string you want to analyze.

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