Eval Commandedit

The eval-model command evaluates model prediction errors in a given time range, with a given model.

For example the command below will evaluate the model named avg_temp2 between yesterday and the current time:

loudml -e "eval-model --from now-1d --to now avg_temp2"

And this example will output result to stdout:

eval(test-model): 100%|███████████████████████████| 1/1 [00:01<00:00,  1.01s/it]
timestamp           @count_value         loudml.count_value
1569570000.0        15217.              15066.361
1569571200.0        14772.              14729.681
1569572400.0        14423.              14171.51
1569573600.0        226.                13703.53

The eval-model command supports the following options:


(date) The from date in range query, supports Date Math notation.


(date) The to date in range query, supports Date Math notation.


Will save output data points to the bucket


Calculate and print the mean square error


Use the specified model version for evaluation. Use -v all with -e flag to evaluate and compare the error for all saved model versions


The model name