Brush C++ API
A flexible interpretable machine learning framework
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#include "../data/data.h"
Go to the source code of this file.
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. | |