If you would like to retrain a previously built model, either by adding new training data or by tinkering with custom parameters (or both!), here is how:
Click on the model you’d like to use as your base model (e.g. “Publication Type Classification Model v2”) You can review the following link to Create a Classification Model.
In the Actions button located in the top right corner, click the Retrain Model option
Adjust your dataset or custom parameters. See Classification Model Performance Metrics for descriptions of each advanced parameter option.
For example, since my classes are small, I found more documents for each class. I also increased my test set size from 10% to 30% and increased the number of epochs from 5 to 10.
Click Train Model and save a new name for this model (“Publication Type Classification v3”)
Once the model has been built, compare the results between this model’s performance metrics and the prior model’s metrics. Continue to tinker until you are satisfied with your model performance, at which point you can publish your model for use within the software (see How to Publish / Unpublish a Classification Model)
