RMSE: Calculate the Root Mean Square Error of a 2 column matrix
In jeanmarcgp/mlStocks: Machine Learning Predictive Analysis for Stocks
Description
Usage
Arguments
Details
Value
Description
Given a two column matrix (typically yhat and y), this function
calculates the root mean square error between y and yhat.
Usage
1
RMSE(mat)
Arguments
mat
The two column matrix used to calculate the mean squared difference.
Details
ssuming N is the number or rows, the calculation for the RMSE
value is done according to the following formula:
√ ∑(yhat - y)^2 / N
Value
Returns the RMS error of the two columns in the matrix.
jeanmarcgp/mlStocks documentation built on May 19, 2019, 12:38 a.m.
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Description Usage Arguments Details Value
Description
Given a two column matrix (typically yhat and y), this function calculates the root mean square error between y and yhat.
Usage
1 | RMSE(mat)
|
Arguments
mat |
The two column matrix used to calculate the mean squared difference. |
Details
ssuming N is the number or rows, the calculation for the RMSE value is done according to the following formula:
√ ∑(yhat - y)^2 / N
Value
Returns the RMS error of the two columns in the matrix.
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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