Add confidence levels
Tweak the confidence level used for historical anomaly detection. By default, if a value falls outside the 99% confidence interval, it is labeled as an anomaly.
Modify this with the level
parameter, which accepts any value between
0 and 100, including decimals.
Increasing the level
results in fewer anomalies detected, while
decreasing the level
increases the number of anomalies detected.
👍 Use an Azure AI endpoint
To use an Azure AI endpoint, set the
base_url
argument:
nixtla_client = NixtlaClient(base_url="you azure ai endpoint", api_key="your api_key")
📘 Available models in Azure AI
If you use an Azure AI endpoint, set
model="azureai"
nixtla_client.detect_anomalies(..., model="azureai")
For the public API, two models are supported:
timegpt-1
andtimegpt-1-long-horizon
.By default,
timegpt-1
is used. See this tutorial for details on usingtimegpt-1-long-horizon
.
For more information, read our detailed tutorial on anomaly detection.
Was this page helpful?