Configure Match and Merge > Training adaptive AI match models
  

Training adaptive AI match models

An adaptive AI match model is part of the match model. You can train an adaptive AI match model to predict whether record pairs are a match or not. A trained adaptive AI match model can analyze data attributes and make match predictions based on its learning.
Before you train an adaptive AI match model, you need to identify the training data set that is a true representation of your organization's data. The results produced by the adaptive AI match model are only as good as the training data set the model is trained on.
During the training process, users label record pairs that are presented to them in batches. The labels indicate whether the record pairs are a match or not. The labeled record pairs are the examples that the model learns from to predict whether record pairs are a match.
To train an adaptive AI match model, use a custom match model that suits your business needs. You create a custom model from a copy of a predefined match model or from scratch.
After you publish a match model, you can define match and merge jobs, and run the jobs. For information about defining and running match and merge jobs, see Define Jobs.