MSE
Returns a table that displays the mean squared error of the prediction and response columns in a linear regression model.
You cannot pass any inputs to the OVER()
clause.
Important: Before using a machine learning function, be aware that all the ongoing transactions might be committed.
Syntax
MSE ( target, prediction) OVER()
Parameters
target |
The response variable for the model. Must be a float. |
prediction |
The output from the PREDICT_LINEAR_REG function. If that output is saved as a table, the column containing the prediction from the function is used. Must be a float. |
Examples
This example shows how you can execute the MSE function on an input table named faithful_testing
. The response variables appear in the column obs
, while the prediction variables appear in the column pred
.
=> SELECT MSE(obs, prediction) OVER() FROM (SELECT eruptions AS obs, PREDICT_LINEAR_REG (waiting USING PARAMETERS model_name='linearRegModel') AS prediction FROM faithful_testing) AS prediction_output; mse | Comments -------------------+----------------------------------------------- 0.244712410708555 | Of 272 rows, 272 were used and 0 were ignored (1 row)