Brush C++ API
A flexible interpretable machine learning framework
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metrics.h File Reference
#include "../data/data.h"
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Namespaces

namespace  Brush
 < nsga2 selection operator for getting the front
 
namespace  Eval
 Namespace containing scoring functions for evaluation metrics.
 
namespace  Brush::Eval
 

Functions

float Brush::Eval::mse (const VectorXf &y, const VectorXf &yhat, VectorXf &loss, const vector< float > &class_weights)
 mean squared error
 
VectorXf Brush::Eval::log_loss (const VectorXf &y, const VectorXf &predict_proba, const vector< float > &class_weights=vector< float >())
 Calculates the log loss between the predicted probabilities and the true labels.
 
float Brush::Eval::mean_log_loss (const VectorXf &y, const VectorXf &predict_proba, VectorXf &loss, const vector< float > &class_weights)
 log loss
 
float Brush::Eval::average_precision_score (const VectorXf &y, const VectorXf &predict_proba, VectorXf &loss, const vector< float > &class_weights=vector< float >())
 Calculates the average precision score between the predicted probabilities and the true labels.
 
VectorXf Brush::Eval::multi_log_loss (const VectorXf &y, const ArrayXXf &predict_proba, const vector< float > &class_weights=vector< float >())
 Calculates the multinomial log loss between the predicted probabilities and the true labels.
 
float Brush::Eval::mean_multi_log_loss (const VectorXf &y, const ArrayXXf &predict_proba, VectorXf &loss, const vector< float > &class_weights=vector< float >())
 Calculates the mean multinomial log loss between the predicted probabilities and the true labels.