# Choosing the item interaction data used for training
<a name="event-values-types"></a>

**Important**  
By default, all new solutions use automatic training. With automatic training, you incur training costs while your solution is active. To avoid unnecessary costs, when you are finished you can [update the solution](updating-solution.md) to turn off automatic training. For information about training costs, see [Amazon Personalize pricing](https://aws.amazon.com/personalize/pricing/).

You can choose the events in an Item interactions dataset that Amazon Personalize uses when creating a solution version (training a model). Choosing item interaction data before training allows you to use only a relevant subset of your data for training or remove noise to train a more optimized model. For more information about Item interactions datasets, see [Item interaction data](interactions-datasets.md).

**Note**  
If you use User-Personalization-v2 or Personalized-Ranking-v2, your training cost is based on your item interactions data before filtering by event type or value. For more information about pricing, see [Amazon Personalize pricing](https://aws.amazon.com/personalize/pricing/). 

You can choose item interaction data as follows:
+ **Choose records based on type** – When you configure a solution, if your Item interactions dataset includes event types in an EVENT\$1TYPE column, you can optionally specify an event type to use in training. For example, if your Item interactions dataset includes *purchase*, *click*, and *watch* event types, and you want Amazon Personalize to train the model with only *watch* events, when you configure your solution, you would provide *watch* as the `event type` that Amazon Personalize uses in training. 

  If you have multiple event types and use the User-Personalization-v2 recipe or Personalized-Ranking-v2 recipe, when you configure a custom solution you can specify different weights for different types. For example, you can configure a solution to give more weight to purchase events than click events. For more information, see [Optimizing a solution with events configuration](optimizing-solution-events-config.md).

   If your Item interactions dataset has multiple event types in an EVENT\$1TYPE column, and you do not provide an event type when you configure your solution, Amazon Personalize uses all item interaction data for training with equal weight regardless of type. 
+ **Choose records based on type and value ** – When you configure a solution, if your Item interactions dataset includes EVENT\$1TYPE and EVENT\$1VALUE fields, you can set a specific value as a threshold to exclude records from training. For example, if your EVENT\$1VALUE data for events with an EVENT\$1TYPE of *watch* is the percentage of a video that a user watched, if you set the event value threshold to 0.5, and the event type to *watch*, Amazon Personalize trains the model using only *watch* interaction events with an EVENT\$1VALUE greater than or equal to 0.5. 

The following code shows how to use the SDK for Python (Boto3) to create a solution that uses only `watch` events where the use watched more than half of the video.

```
import boto3

personalize = boto3.client('personalize')

create_solution_response = personalize.create_solution(
    name = 'solution name',
    datasetGroupArn = 'arn:aws:personalize:region:accountId:dataset-group/datasetGroupName',
    recipeArn = 'arn:aws:personalize:::recipe/aws-user-personalization-v2',
    eventType = 'watch',
    solutionConfig = {
        "eventValueThreshold": "0.5"
    }
)

# Store the solution ARN
solution_arn = create_solution_response['solutionArn']

# Use the solution ARN to get the solution status
solution_description = personalize.describe_solution(solutionArn = solution_arn)['solution']
print('Solution status: ' + solution_description['status'])
```