mse_measure module¶
Mean squared error measure¶
The mse_measure
module
implements the concept of means squared error measures
for machine learning algorithms.
This concept is implemented through the
MSEMeasure
class and
overloads the MLErrorMeasure._compute_measure()
method.
The mean squared error (MSE) is defined by
\[\operatorname{MSE}(\hat{y})=\frac{1}{n}\sum_{i=1}^n(\hat{y}_iy_i)^2,\]
where \(\hat{y}\) are the predictions and \(y\) are the data points.

class
gemseo.mlearning.qual_measure.mse_measure.
MSEMeasure
(algo)[source]¶ Bases:
gemseo.mlearning.qual_measure.error_measure.MLErrorMeasure
Mean Squared Error measure for machine learning.
Constructor.
 Parameters
algo (MLAlgo) – machine learning algorithm.