---
schema_version: "1"
id: f68216d706d9156e13b27b726d326d04ad0e77add7af4047ac289a2eb95440e4
title: Edit Model Settings
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/analytics/264-0-0/bi_edd_model_manager_model_edit.md
canonical_url: https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_manager_model_edit.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: b82d6ae7715f32c73b975de10e92bdf73b594cabb4e0dda3b959fd0bd32f3829
description: You can update model settings that were previously set during model deployment.
products:
  - CRM Analytics
  - Cross Cloud
release: "264"
---
# Edit Model Settings

You can update model settings that were previously set during model deployment.

To edit model settings:

1. [View a Prediction Definition](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_manager_view.htm&release=264.0.0&type=5 "Manage a prediction definition and its associated models.") in Model Manager.
2. [View a Model](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_manager_model_view.htm&release=264.0.0&type=5 "You can view a model deployed in your org.").
    
    ![Model tab in the Edit Model Settings window](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_edd_model_manager_model_view.png)
3. On the **Model Settings** subtab, change the settings you want.
    
     
    | Column | Description |
    | --- | --- |
    | **Model Name** | Change the model's display name. |
    | **Model Threshold** in **Model Details** | For the classification use case, you can update the threshold value for a model. The threshold value tells your model how to classify a binary outcome. To learn more, see [Threshold Evaluation for Binary Classification Use Cases](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_metrics_threshold_evaluation_category.htm&release=264.0.0&type=5 "Threshold Evaluation helps you optimize the threshold value for a model. The threshold value tells your model how to classify a binary outcome. If the calculated probability is above the threshold value, Einstein classifies the outcome one way (such as True or Positive). If the calculated probability is below the threshold value, Einstein classifies the outcome the other way (such as False or Negative)."). |
    | **Object Connection** | If applicable, change the Salesforce object associated with this model, along with the mappings between the model, fields in the Salesforce object, and the dataset column. To learn more, see [Map Model Variables](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_deploy_map.htm&release=264.0.0&type=5 "Define the mapping between variables in the model to fields in the Salesforce object or to columns in the supplemental dataset."). |
    | **Actionable Variables** | If applicable, select actionable variables to trigger Einstein Discovery improvements, which are suggested actions to take to improve predicted outcomes. To learn more, see [Select Actionable Variables for Suggested Improvements](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_deploy_variable.htm&release=264.0.0&type=5 "The suggested improvements from Einstein Discovery are recommendations that users can take action on to improve predicted outcomes. To get suggested improvements, at least one actionable variable must be selected on the model. Actionable variables represent data factors that people can control, such as deciding which marketing campaign to use for a particular customer."). |
    | **Segmentation Filters** | Choose whether to use the model to get predictions on all data, or on just a segment (subset) of the data. To learn more, see [Configure Segmentation Filters](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_deploy_filter.htm&release=264.0.0&type=5 "Choose whether to use the model to get predictions on all data or on just a segment (subset) of the data. For example, you can focus on a specific product model or a group of customers. A prediction definition can contain multiple models in which each model produces predictions for a different segment."). |
4. Save your changes.