[[latest-prerequisites,role=tab-a]]
## Prerequisites
* [Coveo Machine Learning (Coveo ML)](https://docs.coveo.com/en/188/) [Product Recommendation (PR)](https://docs.coveo.com/en/3132/) [models](https://docs.coveo.com/en/1012/) use [Coveo Analytics events](https://docs.coveo.com/en/260/) to relevantly target and suggest products to your [visitors](https://docs.coveo.com/en/nbub9475/).
Therefore, you must [log commerce events](https://docs.coveo.com/en/3188/) to ensure that your commerce interfaces correctly track user interactions.
More specifically, you must log the following event types:
** Product views
** Purchase events
** Cart events (add/remove)
** Click events
> **Notes**
>
> * PR models will work without cart and click events, but you should still log them for accurate reporting and [attribution](https://docs.coveo.com/en/m7l98577/).
>
> * To serve relevant recommendations, a PR model needs at least 10,000 view and/or purchase events to learn from.
* Have configured a [catalog entity](https://docs.coveo.com/en/3143/) and [catalog configuration](https://docs.coveo.com/en/l5if0520/) in your [Coveo organization](https://docs.coveo.com/en/185/).
* Your [catalog data](https://docs.coveo.com/en/obcf0333/) for items of the Product [catalog object](https://docs.coveo.com/en/ncig0154/) contains data for the `ec_category` field.
Otherwise, category-based PR strategies won't function correctly.
We also recommend that you populate the other [commerce standard fields](https://docs.coveo.com/en/n73f0502#standard-commerce-fields) to enhance recommendation precision and diversity.
[[latest-create,role=tab-a]]
## Create a PR model
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page of the [Coveo Administration Console](https://docs.coveo.com/en/183/), click **Add model**, and then click the **Product Recommendations** card.
. Click **Next**.
. Under **Catalog**, select the [catalog entity](https://docs.coveo.com/en/3143/) that contains the products to recommend.
. Under **Tracking IDs**, select the [tracking IDs](https://docs.coveo.com/en/o8rb0139/) that identify the storefronts selling the products from the selected catalog entity.
If the catalog entity is associated with multiple tracking IDs, you can select multiple tracking IDs if you want the model to use usage analytics data from different storefronts, thus increasing the amount of data available for training.
**Example**
If you chose the `Sports` catalog entity, which is associated with the `Sports` and `Outdoor` tracking IDs, you can select both tracking IDs to have the model use usage analytics data from both storefronts.
> **Tip**
>
> Catalog entities and tracking IDs have a one-to-one relationship, which you can view on the [**Storefront associations**](https://platform.cloud.coveo.com/admin/#/orgid/commerce/storefront/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/commerce/storefront/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/commerce/storefront/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/commerce/storefront/)) page of the [Coveo Administration Console](https://docs.coveo.com/en/183/).
. Under **Dataset training type**, select whether you want the model to use [Coveo Analytics data](https://docs.coveo.com/en/259/) gathered from individual products or from product groups:
** **Products**: Leverage usage analytics data from individual products.
The model identifies content using each item's unique content ID (for example, `permanentid`).
** **Product groups**: Leverage usage analytics data aggregated from all products within the same group.
The model uses [grouping fields](https://docs.coveo.com/en/l78i2152#grouping-field-configuration) to identify the content to recommend (for example, `ec_item_group_id`), ignoring the items' unique content ID.
> **Important**
>
> You must configure [product grouping](https://docs.coveo.com/en/l78i2152/) before selecting this option.
> Products without a group ID will be excluded from the training dataset.
. Click **Next**.
. In the **Select the strategies this model will support** section, select the model's [recommendation strategy](https://docs.coveo.com/en/p85e0425/):
** **All strategies** (Recommended): The model is trained to support all available recommendation strategies, allowing for a versatile range of recommendations.
** **Purchase-based strategies**: Choose this option to train the model specifically for strategies that rely on purchase data.
Use this option only if your storefront gathers substantial data.
You'll also have to build a separate model if you want to provide recommendations for view-based strategies.
** **View-based strategies**: Choose this option to train the model specifically for strategies that rely on product view data.
Use this option only if your storefront gathers substantial data.
You'll also have to build a separate model if you want to provide recommendations for purchase-based strategies.
. Click **Next**.
. Under **Name your model and start building**, enter a meaningful display name for the model.
. (Optional) Use the **Project** selector to associate your model with one or more [projects](https://docs.coveo.com/en/n7ef0517/).
. Click **Start building**.
> **Note**
>
> On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, under the **Status** column, in the model row, the value is most probably **Inactive**.
>
> The model value will change to **Active** when the model creation is complete (typically within 30 minutes, depending on the amount of usage analytics data to process).
> The model can only return recommendations when its status is **Active**.
>
> For more information on Coveo ML model statuses, see the [**Status** column reference](#status-column).
. [Associate the model with a pipeline](https://docs.coveo.com/en/p1vg0524/) to use the [model](https://docs.coveo.com/en/1012/) in a Coveo-powered commerce interface.
## Edit a PR model
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the model you want to edit, and then click **Edit** in the Action bar.
. On the subpage that opens, select the **Configuration** tab.
. Under **Name**, you can optionally edit the model's display name.
. (Optional) Use the **Project** selector to associate your model with one or more [projects](https://docs.coveo.com/en/n7ef0517/).
. In the **Define your training dataset** section, you can:
** Add [tracking IDs](https://docs.coveo.com/en/o8rb0139/) to expand the model training data on more storefronts.
Each tracking ID must still leverage the same products contained in the catalog entity chosen when configuring the model.
** Change the **Dataset training type** between **Products** and **Product groups**.
. In the [**Building parameters**](#building-parameters-section) section, you can change the default and recommended **Building frequency** and **Data period**.
. In the **Strategy selection** section, you can view all the trained recommendation strategies and their associated query pipelines.
You can select additional untrained strategies to train, or un-select previously trained strategies.
> **Important**
>
> Be careful when un-selecting a strategy that's already associated with a query pipeline, as this may affect returned results.
. Click **Save**.
> **Note**
>
> Updating the training dataset, building parameters, or strategy selection initiates an automatic model rebuild when you save the model.
> The [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page shows your model's current **Status**.
> Model settings take effect only when its status is **Active**.
>
> For more information on Coveo ML model statuses, see the [**Status** column reference](#status-column).
. [Associate the model with a pipeline](https://docs.coveo.com/en/p1vg0524/) to use the [model](https://docs.coveo.com/en/1012/) in a Coveo-powered commerce interface.
## Edit a PR model JSON configuration
. Access the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
. Click the desired model, and then click **More** > **Edit JSON** in the Action bar.
. In the **Edit a Model JSON Configuration** panel that appears, modify the existing model configuration:
```json
{
"modelDisplayName": "
",
"exportPeriod": "",
"intervalTime": ,
"intervalUnit": "",
"exportOffset": "",
"extraConfig": []
}
```
Where:
* `modelDisplayName` (string) is the name of the model appearing on the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
* `exportPeriod` (ISO-8601 string, _required_) is the period defining the age of the [Coveo Analytics data](https://docs.coveo.com/en/259/) used to build the model.
Must be in the ISO8601 period format (that is, `PyYmMwWdDThHmMsS`).
> **Note**
>
> Unless an [`exportOffset`](https://docs.coveo.com/en/3397#exportoffset) is specified, the `exportPeriod` uses the moment when the model was generated as a base.
* `intervalTime` (integer, _required_) is the number of `intervalUnit` (that is, `DAY`, `WEEK`, or `MONTH`) between each update of the model.
Must be between `1` and `30` inclusively.
* `intervalUnit` (string enum, _required_) is the duration unit of the interval between each update of the model.
See `intervalTime`.
Accepted values are: `DAY`, `WEEK`, and `MONTH`.
* [[exportoffset-pr]] `exportOffset` (ISO-8601 string) is the offset of the usage analytics data used to build the model.
Must be in the ISO8601 period format (that is, `PyYmMwWdDThHmMsS`).
The default value is `PT0S`, meaning that all events are considered when building a model (the `exportPeriod` is based on the moment the model was generated).
**Example**
You want to ignore events that occur on the current day, so you set the `exportOffset` value to `P1D`.
* `extraConfig` (array of string) are additional advanced parameters used to tailor the model to your use case:
** `catalogId` (string) is the identifier of the [catalog entity](https://docs.coveo.com/en/3143/) associated with the model.
** `trackingIds` (array of strings) are the [tracking IDs](https://docs.coveo.com/en/o8rb0139/) identifying the storefronts where [Coveo Analytics data](https://docs.coveo.com/en/259/) is collected to build the model.
** `useProductGroup` (boolean) sets whether the model uses product groups when providing recommendations.
When enabled, the model uses [Coveo Analytics data](https://docs.coveo.com/en/259/) gathered from product groups to provide broader recommendations based on product categories or collections.
The model uses [grouping fields](https://docs.coveo.com/en/l78i2152#grouping-field-configuration) to identify the content to recommend (for example, `ec_item_group_id`), ignoring the items' unique content ID.
Make sure you leverage [product grouping](https://docs.coveo.com/en/l78i2152/) if you set this parameter to `true`.
** `swimlanesToTrain` (array of strings) are the strategy keys defining which recommendation strategies the model should be trained to support.
See [Product recommendation strategies](https://docs.coveo.com/en/p85e0425/) to know which keys to use depending on the strategies you want to support.
. Click **Save** to apply your changes.
## Delete a PR model
> **Note**
>
> If the model is associated with a query pipeline, make sure to dissociate the model from the query pipeline after deleting it.
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the ML model that you want to delete, and then click **More** > **Delete** in the Action bar.
. In the panel that appears, click **Delete**.
## Review model information
On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the desired model, and then click **View** in the Action bar.
For more information, see [Reviewing model information](https://docs.coveo.com/en/1894/).
[[latest-reference,role=tab-a]]
## "Status" column
On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page of the [Administration Console](https://docs.coveo.com/en/183/), the **Status** column indicates the current state of your Coveo ML models.
The following table lists the possible model statuses and their definitions:
[%header,cols="1,6,^.^1"]
|===
.^|Status
.^|Definition
|Status icon
|Active
|The model is active and available.
a|
|Build in progress
|The model is currently building.
a|
|Inactive
|The model isn't ready to be queried, such as when a model was recently created or the organization is offline.
Click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Limited
|Build issues exist that may affect model performance.
Click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Soon to be archived
|The model will soon be archived because it hasn't been queried for an extended period of time.
Click **Delete** to remove the model.
[Learn more about archived models](https://docs.coveo.com/en/mb3e0324/).
a|
|Error
|An error prevented the model from being built successfully.
If it's a temporary system error, check back soon.
Otherwise, click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Archived
|The model was archived because it hasn't been queried for an extended period of time.
Click **Delete** to remove the model.
[Learn more about archived models](https://docs.coveo.com/en/mb3e0324/).
a|
|===
## "Building parameters" section
Set the Coveo ML model training **Building frequency** based on the **Data Period** value. Less frequent for a larger **Data Period** and more frequent for a smaller **Data Period** as recommended in the following table.
[cols="^3,^1,^1,^1"]
|===
.2+.^h|**Data period**
3+h|**Building frequency**
h|Daily
h|Weekly
h|Monthly
|1 month
|[check]
|[check]
|
|3 months (Recommended)
|
|[check]
|
|6 months
|
|
|[check]
|===
The more data the model has access to and learns from, the better the recommendations.
As a general guide, your usage analytics dataset should minimally contain 10,000 commerce events (views and purchases).
With this amount of commerce events, the model will start recommending results.
A model with fewer than 10,000 commerce events will be considered degraded.
The model automatically retrains itself on the schedule you define with the **Building frequency** setting, using the most recent usage analytics data from the **Data period** you specified.
## Required privileges
By default, members with the [required privileges](https://docs.coveo.com/en/1832#required-privileges) can view and edit elements of the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
The following table indicates the privileges required to use elements of the **Models** page and associated panels (see [Manage privileges](https://docs.coveo.com/en/3151/) and [Privilege reference](https://docs.coveo.com/en/1707/)).
[cols="3",options="header"]
|===
|Action
|Service - Domain
|Required access level
|View models
|Machine Learning - Models
Organization - Organization
Search - Query pipelines
|View
.2+|Edit models
|Organization - Organization
Search - Query pipelines
|View
|Machine Learning - Models
|Edit
|===
[[legacy-intro,role=tab-b]]
## About earlier version models
Earlier version models can no longer be created.
This section remains for reference on managing existing earlier version models.
## Edit a PR model
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the model you want to edit, and then click **Edit** in the Action bar.
. On the subpage that opens, select the **Configuration** tab.
. Under **Name**, you can optionally edit the model's display name.
. (Optional) Use the **Project** selector to associate your model with one or more [projects](https://docs.coveo.com/en/n7ef0517/).
. (Optional) In the [**Learning interval**](#learning-interval-section) section, you can change the default and recommended **Data period** and **Building frequency**.
. (Optional) In the **Apply filters on dataset** section, you can add filters to refine the data that the model uses to make its recommendations.
By narrowing down the dataset that a model uses, you can better customize relevancy for specific user groups and use cases.
You can apply filters on all events, or on every event that belongs to a specific category, such as search, click, view, or custom events.
**Example**
You want your PR model to return recommendations that pertain to a specific user group, so you add a data filter to ensure that only a specific set of analytics are used by the model for training purposes.
.. In the **Select a dimension** dropdown menu, select the dimension on which you want to base the learning of the model.
.. In the **Select an operator** dropdown menu, select the appropriate operator.
.. In the **Select value(s)** dropdown menu, add, type, or select the appropriate value.
.. You can optionally add other filters by clicking **Add**.
. (Optional) Configure [advanced settings](#legacy-advanced-config) for your model.
. Click **Save**.
> **Note**
>
> Some configuration changes initiate an automatic model rebuild when you save the model.
> The [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page shows your model's current **Status**.
> Model settings take effect only when its status is **Active**.
>
> For more information on Coveo ML model statuses, see the [**Status** column reference](#status-column).
. [Associate the model with a pipeline](https://docs.coveo.com/en/p1vg0524/) to use the [model](https://docs.coveo.com/en/1012/) in a Coveo-powered commerce interface.
## Edit a PR model JSON configuration
. Access the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
. Click the desired model, and then click **More** > **Edit JSON** in the Action bar.
. In the **Edit a Model JSON Configuration** panel that appears, modify the existing model configuration:
```json
{
"modelDisplayName": "
",
"exportPeriod": "",
"intervalTime": ,
"intervalUnit": "",
"commonFilter": "",
"customEventFilter": "",
"exportOffset": "",
"searchEventFilter": "",
"viewEventFilter": "",
"extraConfig": [],
}
```
Where:
* `modelDisplayName` (string) is the name of the model appearing on the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
* `exportPeriod` (ISO-8601 string, _required_) is the period defining the age of the [Coveo Analytics data](https://docs.coveo.com/en/259/) used to build the model.
Must be in the ISO8601 period format (that is, `PyYmMwWdDThHmMsS`).
> **Note**
>
> Unless an [`exportOffset`](https://docs.coveo.com/en/3397#exportoffset) is specified, the `exportPeriod` uses the moment when the model was generated as a base.
* `intervalTime` (integer, _required_) is the number of `intervalUnit` (that is, `DAY`, `WEEK`, or `MONTH`) between each update of the model.
Must be between `1` and `30` inclusively.
* `intervalUnit` (string enum, _required_) is the duration unit of the interval between each update of the model.
See `intervalTime`.
Accepted values are: `DAY`, `WEEK`, and `MONTH`.
* `commonFilter` (string) is the filter to apply to the common event dimensions (shared by all event types) in the export. Multiple filter parameters are joined with the `AND` operator.
* `customEventFilter` (string) is the filter to apply to the custom event dimensions in the export. Multiple filter parameters are joined with the `AND` operator.
* [[exportoffset]] `exportOffset` (ISO-8601 string) is the offset of the usage analytics data used to build the model.
Must be in the ISO8601 period format (that is, `PyYmMwWdDThHmMsS`).
The default value is `PT0S`, meaning that all events are considered when building a model (the `exportPeriod` is based on the moment the model was generated).
**Example**
You want to ignore events that occur on the current day, so you set the `exportOffset` value to `P1D`.
* `searchEventFilter` (string) is the filter to apply to the click and search event dimensions in the export. Multiple filter parameters are joined with the `AND` operator.
* `viewEventFilter` (string) is the filter to apply to the view event dimensions (shared by all event types) in the export. Multiple filter parameters are joined with the `AND` operator.
* `extraConfig` (array of string) are additional [advanced parameters](#advanced-json-model-parameters) used to tailor the model to your use case.
. Click **Save** to apply your changes.
## Delete a PR model
> **Note**
>
> If the model is associated with a query pipeline, make sure to dissociate the model from the query pipeline after deleting it.
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the ML model that you want to delete, and then click **More** > **Delete** in the Action bar.
. In the panel that appears, click **Delete**.
## Review model information
On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the desired model, and then click **View** in the Action bar.
For more information, see [Reviewing model information](https://docs.coveo.com/en/1894/).
[[legacy-reference,role=tab-b]]
## Advanced configuration
You can configure advanced settings for your [model](https://docs.coveo.com/en/1012/) to suit specific use cases.
Some advanced settings are available from the [model](https://docs.coveo.com/en/1012/) options in the [Administration Console](https://docs.coveo.com/en/183/), while others are only available through JSON configuration parameters.
> **Notes**
>
> * Additional model configurations can be specified through the [Advanced Model Configuration API](https://docs.coveo.com/en/l3od9093/).
>
> * You can also use the [`mlParameters` query parameter](https://docs.coveo.com/en/13#operation/searchUsingPost-mlParameters) to adjust the way your Coveo ML models are used at query time.
To specify advanced settings
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the model for which you want to specify advanced settings.
. Do one of the following:
* To specify an advanced setting using an [Administration Console](https://docs.coveo.com/en/183/) [model](https://docs.coveo.com/en/1012/) option:
.. Click **Edit** in the Action bar.
.. Click the **Advanced** tab, and then in the **Advanced** page left menu, select the setting to configure:
* To specify an advanced setting using a JSON parameter:
.. In the Action bar, click **More**, and then click **Edit JSON**.
.. Enter the advanced parameter configuration in the JSON's `extraConfig` object:
[start=3]
. Click **Save**.
## Advanced model options
### Test configuration mode
> **Note**
>
> The **Test configuration mode** advanced option is available only for sandbox organizations.
[Sandbox organizations](https://docs.coveo.com/en/2959#sandbox-organization) typically lack the amount of usage analytics data that's required to train a model.
The **Test configuration mode** option lets you build a model in a sandbox organization with little or infrequent usage analytics data so you can test the model.
When activated, this option reduces the amount of analytics data that's required to build the model.
It also reduces other frequency thresholds that discard queries or clicks that weren't performed frequently enough.
> **Note**
>
> The usage of certain frequency thresholds, or the selection of a specific value for these frequency thresholds depends on the configuration and implementation of the model.
> As the possible combinations of threshold configurations are adapted for each model, these frequency thresholds aren't listed in this section.
To activate the test configuration mode
. On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page, click the model for which you want to activate the test configuration mode, and then click **Edit** in the Action bar.
. On the subpage that opens, select the **Advanced** tab.
. In the left menu of the **Advanced** tab, select **Test configuration mode**.
. Select the **Activate test configuration mode** checkbox.
. Click **Save**.
## Advanced JSON model parameters
### `recommendProductGroup` (boolean)
Sets whether the model recommends [product groups](https://docs.coveo.com/en/l78i2152/) rather than individual items.
When set to `true`, the model uses [grouping fields](https://docs.coveo.com/en/l78i2152#grouping-field-configuration) to identify the content to recommend, ignoring the items' unique content ID (for example, `permanentid`).
To set the parameter
[Access the model's JSON editor](#advanced-configuration), and then add the parameter configuration to the `extraConfig` object.
**Example**
You want your model to use groups of products rather than individual items when providing recommendations.
Therefore, you enter the following configuration in the `extraConfig` object:
```json
"extraConfig": {
"recommendProductGroup": true
}
```
## "Status" column
On the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page of the [Administration Console](https://docs.coveo.com/en/183/), the **Status** column indicates the current state of your Coveo ML models.
The following table lists the possible model statuses and their definitions:
[%header,cols="1,6,^.^1"]
|===
.^|Status
.^|Definition
|Status icon
|Active
|The model is active and available.
a|
|Build in progress
|The model is currently building.
a|
|Inactive
|The model isn't ready to be queried, such as when a model was recently created or the organization is offline.
Click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Limited
|Build issues exist that may affect model performance.
Click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Soon to be archived
|The model will soon be archived because it hasn't been queried for an extended period of time.
Click **Delete** to remove the model.
[Learn more about archived models](https://docs.coveo.com/en/mb3e0324/).
a|
|Error
|An error prevented the model from being built successfully.
If it's a temporary system error, check back soon.
Otherwise, click **See more details** for additional information (see [Review model information](https://docs.coveo.com/en/1894/)).
a|
|Archived
|The model was archived because it hasn't been queried for an extended period of time.
Click **Delete** to remove the model.
[Learn more about archived models](https://docs.coveo.com/en/mb3e0324/).
a|
|===
## "Learning Interval" section
In this section, you can modify the following:
* [[data-period]]**Data period**: The usage analytics data time interval on which the model will be based.
* **Building frequency**: The rate at which the model is retrained.
Set the Coveo ML model training **Building frequency** based on the **Data Period** value. Less frequent for a larger **Data Period** and more frequent for a smaller **Data Period** as recommended in the following table.
[cols="^3,^1,^1,^1"]
|===
.2+.^h|**Data period**
3+h|**Building frequency**
h|Daily
h|Weekly
h|Monthly
|1 month
|[check]
|[check]
|
|3 months (Recommended)
|
|[check]
|
|6 months
|
|
|[check]
|===
The more data the model has access to and learns from, the better the recommendations. As a general guide, a usage analytics dataset of 10,000 [queries](https://docs.coveo.com/en/231/) or more typically allows a Coveo ML model to provide very relevant recommendations. You can look at your [Coveo Analytics](https://docs.coveo.com/en/182/) data to evaluate the volume of queries on your search hub, and ensure that your Coveo ML models are configured with a training **Data period** that corresponds to at least 10,000 queries. When your [search hub](https://docs.coveo.com/en/1342/) serves a very high volume of queries, you can consider reducing the data period so that the model learns only more recent user behavior and be more responsive to trends.
A Coveo ML model regularly retrains on a more recent Coveo UA dataset, as determined by the **Building frequency** and **Data period** settings, to ensure that the model remains up-to-date with the most recent user behavior.
> **Note**
>
> If you're testing the model in a sandbox environment in which very little analytics data is available to train the model, you can activate the **Test configuration mode** [advanced option](#test-configuration-mode) to ensure the model provides recommendations.
## Required privileges
By default, members with the [required privileges](https://docs.coveo.com/en/1832#required-privileges) can view and edit elements of the [**Models**](https://platform.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) ([platform-ca](https://platform-ca.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-eu](https://platform-eu.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/) | [platform-au](https://platform-au.cloud.coveo.com/admin/#/orgid/ai-and-ml/models/)) page.
The following table indicates the privileges required to use elements of the **Models** page and associated panels (see [Manage privileges](https://docs.coveo.com/en/3151/) and [Privilege reference](https://docs.coveo.com/en/1707/)).
[cols="3",options="header"]
|===
|Action
|Service - Domain
|Required access level
|View models
|Machine Learning - Models
Organization - Organization
Search - Query pipelines
|View
.2+|Edit models
|Organization - Organization
Search - Query pipelines
|View
|Machine Learning - Models
|Edit
|===