Root Mean Square Error (RMSE)

The root mean square error (RMSE) is a performance measure often used to evaluate machine learning regression models by determining the similarity between two sets. The formula for RMSE is:

Where $X$ is a matrix containing all of the feature values (excluding labels) in the test dataset with one row per instance, $h$ is the prediction function, $m$ is the number of records in the validation dataset, $X^{(i)}$ is a vector of all feature values of the i^th instance (within $X$), and $y^{(i)}$ is a vector of all the desired outputs (the labels).

Broader Topics Related to Root Mean Square Error (RMSE)

Regression Learning

A type of machine learning that classifies entities based on their characteristics