gemseo / mlearning / qual_measure

# 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

$\operatorname{MSE}(\hat{y})=\frac{1}{n}\sum_{i=1}^n(\hat{y}_i-y_i)^2,$

where $$\hat{y}$$ are the predictions and $$y$$ are the data points.

class gemseo.mlearning.qual_measure.mse_measure.MSEMeasure(algo)[source]

Mean Squared Error measure for machine learning.

Constructor.

Parameters

algo (MLAlgo) – machine learning algorithm.