Predictive coding module for Advanced eDiscovery (preview)
Using the new predictive coding module in Advanced eDiscovery, you can create and build a model to prioritize review of documents starting with the most relevant documents. To get started, you can create a model, label as few as 50 documents, and then filter documents by model prediction scores to review relevant non-relevant documents.
Here’s a quick overview of the workflow:
Open the predictive coding module in a review set.
On the Predictive coding models page, click New model to create a new predictive coding model.
Label at least 50 documents as Relevant or Not relevant. This labeling is used to train the system.
Apply the Prediction score filter for your model to the review set. To do this:
In the review set, click Filters.
In the Filters flyout page, expand the Analytics/ML section and then select Prediction score checkbox for the model you want to apply.
In the Prediction score filter, specify a prediction score. The filter will display the documents in the review set that match the prediction score.
Monitor the performance, status, and stability of your model.