Classifier Models Overview
A classifier model is a reference data object in a content set. Use a classifier model to analyze long text strings that contain multiple values. A classifier model identifies the most common type of information in each string.
You add a classifier model to a Classifier transformation. The transformation searches for common values between the classifier model data and the data in each input row. The transformation uses the common values to categorize the type of information that each row represents.
You use a classifier model when the input data has the following characteristics:
- •The input data contains text. Classifier models apply natural language processes to text data to identify the types of information in the text. Natural language processes detect relevant words in the input string. Natural language processes disregard words that are not relevant.
- •The input data strings contain multiple values. For example, you can create a data column that contains the contents of an email message in each field.
The Classifier transformation reads string datatypes. The transformation imposes no limit on the length of the input strings.
You compile classifier models in the Developer tool. When you compile a model, you create associations between similar data values in the model. The Classifier transformation uses the compiled data to search for information in the input data.