Rmse

What Rmse is

Root Mean Square Error (RMSE) is a measure of the difference between values predicted by a model or an estimator and the true values. It is used to measure the accuracy of a model by taking the average of the squares of the differences between the predicted values and the actual values.

Steps for calculating RMSE:

1. Calculate the difference between the predicted values and the actual values for each observation.

2. Square the difference for each observation.

3. Sum the squared differences.

4. Divide the sum of the squared differences by the number of observations.

5. Take the square root of the result.

6. The result is the RMSE.

Examples

1. RMSE is often used to evaluate the accuracy of a model that predicts continuous outcomes, such as predicting a house price.

2. RMSE can be used to measure the performance of a forecasting model, such as predicting future sales of a product.

3. RMSE is commonly used as an error metric in regression problems, such as predicting a customer’s risk of defaulting on a loan.

Related Topics

• ESTIMATOR

• ACCURACY

• MEAN

• CONTINUOUS

• REGRESSION

• AVERAGE