MSE
Returns a table that displays the mean squared error of the prediction and response columns in a machine learning model.
Returns a table that displays the mean squared error of the prediction and response columns in a machine learning model.
Syntax
MSE ( targets, predictions ) OVER()
Arguments
targets
- The model response variable, of type FLOAT.
predictions
- A FLOAT input column that contains predicted values for the response variable.
Examples
Execute the MSE function on input table faithful_testing
. The response variables appear in the column obs
, while the prediction variables appear in the column prediction
.
=> SELECT MSE(obs, prediction) OVER()
FROM (SELECT eruptions AS obs,
PREDICT_LINEAR_REG (waiting USING PARAMETERS model_name='myLinearRegModel') AS prediction
FROM faithful_testing) AS prediction_output;
mse | Comments
-------------------+-----------------------------------------------
0.252925741352641 | Of 110 rows, 110 were used and 0 were ignored
(1 row)