|Logistic regression model creation 1||
The first 10 GB of data processed by
|Linear regression model creation 1|
|K-means clustering model creation 1|
|Time series model creation 1, 2|
|AutoML Tables model creation 1||
The total cost of a job is the sum of the following two costs:
|DNN model creation 1|
|Boosted tree model creation|
|Matrix factorization model creation||Not supported||Matrix factorization is only available to flat-rate customers or customers with reservations. On-demand customers are encouraged to use flex slots to use matrix factorization.|
|Evaluation, inspection, and prediction (all model types)||Charges from evaluation, inspection, and prediction queries are included in the 1 TB of data per month under the BigQuery analysis free tier.|
CREATE MODEL statement stops at 50 iterations
for iterative models.
2 For time series models, when auto-arima is enabled for
automatic hyper-parameter tuning, multiple candidate models are fitted and
evaluated during the training phase. In this case, the number of bytes
processed by the input
SELECT statement is multiplied by the
number of candidate models, which can be controlled by the
For single time series forecasting with auto-arima enabled, when
AUTO_ARIMA_MAX_ORDERis (2, 3, 4, 5), the number of candidate models is (12, 20, 30, 42) respectively if non-seasonal _d_ equals one; otherwise, the number of candidate models is (6, 10, 15, 21).
For multiple time series forecasting using
TIME_SERIES_ID_COL, the charge is for (12, 20, 30, 42) candidate models when
AUTO_ARIMA_MAX_ORDERis (2, 3, 4, 5) respectively.
Note that this model selection only applies to model creation. For model evaluation, inspection, and prediction, only the selected model is used, with regular query pricing.