measure_mse_score: Measure mean squared error.
In easyml: Easily Build and Evaluate Machine Learning Models
Description
Usage
Arguments
Value
See Also
Description
Given the ground truth (correct) target values and the estimated target
values, calculates the mean squared error metric.
Usage
1
measure_mse_score(y_true, y_pred)
Arguments
y_true
A numeric vector; the ground truth (correct) target values.
y_pred
A numeric vector; the estimated target values.
Value
A numeric vector of length one; the mean squared error metric.
See Also
Other measure: measure_auc_score,
measure_correlation_score,
measure_r2_score
easyml documentation built on June 26, 2017, 9:02 a.m.
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Description Usage Arguments Value See Also
Description
Given the ground truth (correct) target values and the estimated target values, calculates the mean squared error metric.
Usage
1 | measure_mse_score(y_true, y_pred)
|
Arguments
y_true |
A numeric vector; the ground truth (correct) target values. |
y_pred |
A numeric vector; the estimated target values. |
Value
A numeric vector of length one; the mean squared error metric.
See Also
Other measure: measure_auc_score,
measure_correlation_score,
measure_r2_score
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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