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Uploading data for training and testing of the topic detection model

Suggest edit Updated on April 5, 2022

Upload sample records to train the model and to test whether the model assigns the topics correctly.

Before you begin: Prepare a .csv, .xls, or .xlsx file with training and testing data, for example, previous customer messages that have assigned categories.

Tip: To view the structure required for the training and testing data as well as the sample records, in the Source selection wizard step, click Download template.

  1. In the Source selection wizard step, click Choose file.
  2. Select a .csv, .xls, or .xlsx file with sample records for training and testing the model.
    Ensure that the file contains sample records with assigned categories.
  3. Optional: To enable spellchecking, perform the following actions:
    1. Select the Use spell checking check box.
    2. To increase the accuracy of the model by correcting any spelling errors, expand the Select spell checker list, and then select a Spelling Checker Decision Data rule, if available.
    Caution: Enabling spellchecking can significantly increase the model training time, depending on the size of the training sample. Spellchecking also has an impact on real-time performance of the model.
  4. Click Next.
What to do next: Split the uploaded data into a set for training the model and a set for testing the model accuracy. For more information, see Defining the training and testing samples for topic detection.
  • Previous topic Defining a taxonomy for machine learning topic detection
  • Next topic Defining the training and testing samples for topic detection
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