slope 0.31.0
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Public Member Functions | List of all members
slope::MSE Class Reference

Mean Squared Error (MSE) scoring metric. More...

#include <score.h>

Inheritance diagram for slope::MSE:
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Collaboration diagram for slope::MSE:
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Public Member Functions

double eval (const Eigen::MatrixXd &eta, const Eigen::MatrixXd &y, const std::unique_ptr< Loss > &) const override
 
- Public Member Functions inherited from slope::MinimizeScore
bool isWorse (double a, double b) const override
 
double initValue () const override
 
- Public Member Functions inherited from slope::Score
std::function< bool(double, double)> getComparator () const
 

Additional Inherited Members

- Static Public Member Functions inherited from slope::Score
static std::unique_ptr< Score > create (const std::string &metric)
 

Detailed Description

Mean Squared Error (MSE) scoring metric.

Computes the average squared difference between predictions and true responses. Inherits from MinimizeScore since lower MSE values indicate better fit.

MSE = (1/n) Σ(y_i - η_i)² where:

  • n is the number of samples
  • y_i is the true response for sample i
  • η_i is the predicted response for sample i

Definition at line 159 of file score.h.

Member Function Documentation

◆ eval()

double slope::MSE::eval ( const Eigen::MatrixXd &  eta,
const Eigen::MatrixXd &  y,
const std::unique_ptr< Loss > &   
) const
overridevirtual

Evaluates the MSE between predictions and true responses.

Parameters
etaMatrix of model predictions
yMatrix of true responses
Returns
Computed MSE value

Implements slope::Score.

Definition at line 127 of file score.cpp.

The documentation for this class was generated from the following files: