The new anomaly detection capabilities in BigQuery ML that leverage unsupervised machine learning to help you detect anomalies without needing labeled data is here.
Depending on whether or not the training data is time series, users can now detect anomalies in training data or on new input data using a new ML.DETECT_ANOMALIES
function (documentation), with the following models:
-
Autoencoder model, now in Public Preview (documentation)
-
K-means model, already GA (documentation)
-
ARIMA_PLUS time series model, already GA (documentation)
The function runs against time-series data using ARIMA_PLUS
models using AUTOENCODER
and KMEANS
models.
Read the article here