Training the Model Flow
When you train a model, you identify records as matches or non-matches by answering a series of questions.
Objectives
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When you train a model, you identify records as matches or non-matches by answering a series of questions.
The following image shows that the environment is setting up the training session:
While the training session is being set up, you can navigate to other parts of the application by clicking on the link highlighted in the image above. If you navigate back to the application, the status of the model flow changes to Preparing training and then to Ready to train as shown in the following image:
When the training session is ready, a notification appears with a link to start the training, as seen in the following image:
A series of questions appear and for each pair, you have to confirm whether the pair is the same or different. If you are not sure about the pair, you can also mark it as NOT SURE. The following images show some examples of questions:
After answering some questions, if you continuously see questions showing pairs that are likely to be possible matches, you can end the training. At this point, the model flow is trained for matching.
The following image appears where you can choose to continue with the training or start matching:
At this point, the model is being prepared before it can start matching. Once the model is prepared, matching is triggered. Matching implies running the trained model against the tenant dataset to ensure that a user can review the match results to ascertain whether the model is able to deliver the expected results. This matching is different compared to matching by a published model. The match results by a published model appear on Hub associated with a Match IQ badge. When matching is complete, the model moves to the Review swim lane.
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