Creating a Natural Language Classifier model
You can train IBM Watson Natural Language Classifier models with your own training text to meet your specific text-analysis goals. This topic describes how to use the Natural Language Classifier model builder in IBM Watson Studio to create a classifier.
Demonstration
Watch this video to see how to create and train a Natural Language Classifier model using customer support ticket text examples to classify loan types.

Procedure
- Prepare your text training data
Collect a minimum of three example text passages for each of a minimum of two classes in a .csv file, and then upload the file to your project.
 - Train your model
In the Natural Language Classifier model builder, define your classes and add text examples.
 - Test your trained model
After your model is trained, you can use the Test area of the model builder to classify test text passages using your model.
 - (Optional) Retrain your model
You can improve the performance of your model by adding or removing training data and then retraining the model.
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