Amazon Forecast is no longer available to new customers. Existing customers of Amazon Forecast can continue to use the service as normal. [Learn more"](https://aws.amazon.com/blogs/machine-learning/transition-your-amazon-forecast-usage-to-amazon-sagemaker-canvas/)

# Viewing Monitoring Results
<a name="predictor-monitoring-results"></a>

After you generate a forecast and then import more data, you can view the results of predictor monitoring. You can see a visualization of results with the Forecast console or you can programmatically retrieve results with the [ListMonitorEvaluations](API_ListMonitorEvaluations.md) operation. 

 The Forecast console displays graphs of results for each [predictor metric](metrics.md). Graphs include how each metric has changed over the lifetime of your predictor and predictor events, such as retraining. 

 The [ListMonitorEvaluations](API_ListMonitorEvaluations.md) operation returns metric results and predictor events for different windows of time. 

------
#### [ Console ]

**To view predictor monitoring results**

1. Sign in to the AWS Management Console and open the Amazon Forecast console at [https://console.aws.amazon.com/forecast/](https://console.aws.amazon.com/forecast/).

1. From **Dataset groups**, choose your dataset group.

1. In the navigation pane, choose **Predictors**.

1. Choose the predictor and choose the **Monitoring** tab. 
   +  The **Monitoring results** section shows how different accuracy metrics have changed over time. Use the dropdown list to change which metric the graph tracks.
   + The **Monitoring history** section lists the details for the different events tracked in the results.

    The following is an example of a graph of how the `Avg wQL` score for a predictor has changed over time. In this graph, notice that the `Avg wQL` value is increasing over time. This increase indicates that the predictor accuracy is decreasing. Use this information to determine whether you need to revalidate the model and take action.  
![Graph showing Avg wQL increasing from 0.15 to 0.27 while baseline remains flat at 0.22.](http://docs.aws.amazon.com/forecast/latest/dg/images/predictor-drift.png)

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#### [ SDK for Python (Boto3) ]

 To get monitoring results with the SDK for Python (Boto3), use the `list_monitor_evaluations` method. Provide the Amazon Resource Name (ARN) of the monitor, and optionally specify the maximum number of results to retrieve with the `MaxResults` parameter. Optionally specify a `Filter` to filter results. You can filter evaluations by a `EvaluationState` of either `SUCCESS` or `FAILURE`. The following code gets at maximum 20 successful monitoring evaluations. 

```
import boto3
                            
forecast = boto3.client('forecast')

monitor_results = forecast.list_monitor_evaluations(
    MonitorArn = '{{monitor_arn}}',
    MaxResults = 20,
    Filters = [ 
      { 
         "Condition": "IS",
         "Key": "EvaluationState",
         "Value": "SUCCESS"
      }
   ]
)
print(monitor_results)
```

 The following is an example JSON response. 

```
{
  "NextToken": "string",
  "PredictorMonitorEvaluations": [
    {
      "MonitorArn": "MonitorARN",
      "ResourceArn": "PredictorARN",
      "EvaluationTime": "2020-01-02T00:00:00Z",
      "EvaluationState": "SUCCESS",
      "WindowStartDatetime": "2019-01-01T00:00:00Z",
      "WindowEndDatetime": "2019-01-03T00:00:00Z",
      "PredictorEvent": {
        "Detail": "Retrain",
        "Datetime": "2020-01-01T00:00:00Z"
      },
      "MonitorDataSource": {
        "DatasetImportJobArn": "arn:aws:forecast:{{region}}:{{accountNumber}}:dataset-import-job/{{*}}",
        "ForecastArn": "arn:aws:forecast:{{region}}:{{accountNumber}}:forecast/{{*}}",
        "PredictorArn": "arn:aws:forecast:{{region}}:{{accountNumber}}:predictor/{{*}}",
      
      },
      "MetricResults": [
        {
          "MetricName": "AverageWeightedQuantileLoss",
          "MetricValue": 0.17009070456599376
        },
        {
          "MetricName": "MAPE",
          "MetricValue": 0.250711322309796
        },
        {
          "MetricName": "MASE",
          "MetricValue": 1.6275608734888485
        },
        {
          "MetricName": "RMSE",
          "MetricValue": 3100.7125081405547
        },
        {
          "MetricName": "WAPE",
          "MetricValue": 0.17101159704738722}
      ]
    }
  ]
}
```

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