Rmse: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Calculate Root Mean Square Difference(Error). | Calculate Root Mean Square Difference (Error). | ||
===Synopsis=== | ===Synopsis=== | ||
:err = rmse(y1, | :err = rmse(y1,y2) | ||
===Description=== | ===Description=== | ||
| Line 12: | Line 11: | ||
RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vector or matrix is from a model estimation and measurements then the output is the Root Mean Square Error (RMSE). | RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vector or matrix is from a model estimation and measurements then the output is the Root Mean Square Error (RMSE). | ||
The output '''err''' depends on the input, and there are 3 possible cases, outlined below: | |||
====Inputs and Outputs==== | |||
* '''Case A):''' '''y1''' is a matrix or vector | |||
: err = rmse(y1); | |||
: The output '''err''' is the root mean square of the elements of y1. | |||
* '''Case B):''' '''y1''' is a matrix or vector, '''y2''' is the same size as '''y1''' | |||
: err = rmse(y1,y2); | |||
: The output '''err''' is the root mean square of the difference between y1 and y2. | |||
The output err is the root mean square of the difference between each column of y1 and y2. | * '''Case C):''' '''y1''' is a matrix or vector, '''y2''' is a column vector | ||
: err = rmse(y1,y2); | |||
: The output err is the root mean square of the difference between each column of y1 and y2. | |||
For example, y2 is a reference and the | : Example: For example, '''y2''' is a reference and the rmse is calculated between each column of '''y1''' and the vector '''y2'''. | ||
===See Also=== | ===See Also=== | ||
[[crossval]] | [[crossval]] | ||
Revision as of 09:57, 9 October 2008
Purpose
Calculate Root Mean Square Difference (Error).
Synopsis
- err = rmse(y1,y2)
Description
RMSE is used to calculate the root mean square difference between two vectors or matrices. If the vector or matrix is from a model estimation and measurements then the output is the Root Mean Square Error (RMSE).
The output err depends on the input, and there are 3 possible cases, outlined below:
Inputs and Outputs
- Case A): y1 is a matrix or vector
- err = rmse(y1);
- The output err is the root mean square of the elements of y1.
- Case B): y1 is a matrix or vector, y2 is the same size as y1
- err = rmse(y1,y2);
- The output err is the root mean square of the difference between y1 and y2.
- Case C): y1 is a matrix or vector, y2 is a column vector
- err = rmse(y1,y2);
- The output err is the root mean square of the difference between each column of y1 and y2.
- Example: For example, y2 is a reference and the rmse is calculated between each column of y1 and the vector y2.