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Added more helper methods to Cost.

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Relintai 2023-02-04 13:19:01 +01:00
parent b004a092b7
commit fd13337eb7
2 changed files with 227 additions and 0 deletions
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195
mlpp/cost/cost.cpp
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@ -585,6 +585,186 @@ Ref<MLPPVector> MLPPCost::dual_form_svm_deriv(const Ref<MLPPVector> &alpha, cons
return alg.subtractionm(alphaQDeriv, one); return alg.subtractionm(alphaQDeriv, one);
} }
MLPPCost::VectorCostFunctionPointer MLPPCost::get_cost_function_ptr_normal_vector(const MLPPCost::CostTypes cost) {
switch (cost) {
case COST_TYPE_MSE:
return &MLPPCost::msev;
case COST_TYPE_RMSE:
return &MLPPCost::rmsev;
case COST_TYPE_MAE:
return &MLPPCost::maev;
case COST_TYPE_MBE:
return &MLPPCost::mbev;
case COST_TYPE_LOGISTIC_LOSS:
return &MLPPCost::log_lossv;
case COST_TYPE_CROSS_ENTROPY:
return &MLPPCost::cross_entropyv;
case COST_TYPE_HINGE_LOSS:
return &MLPPCost::hinge_lossv;
case COST_TYPE_WASSERSTEIN_LOSS:
return &MLPPCost::wasserstein_lossv;
default:
return NULL;
}
}
MLPPCost::MatrixCostFunctionPointer MLPPCost::get_cost_function_ptr_normal_matrix(const MLPPCost::CostTypes cost) {
switch (cost) {
case COST_TYPE_MSE:
return &MLPPCost::msem;
case COST_TYPE_RMSE:
return &MLPPCost::rmsem;
case COST_TYPE_MAE:
return &MLPPCost::maem;
case COST_TYPE_MBE:
return &MLPPCost::mbem;
case COST_TYPE_LOGISTIC_LOSS:
return &MLPPCost::log_lossm;
case COST_TYPE_CROSS_ENTROPY:
return &MLPPCost::cross_entropym;
case COST_TYPE_HINGE_LOSS:
return &MLPPCost::hinge_lossm;
case COST_TYPE_WASSERSTEIN_LOSS:
return &MLPPCost::wasserstein_lossm;
default:
return NULL;
}
}
MLPPCost::VectorDerivCostFunctionPointer MLPPCost::get_cost_function_ptr_deriv_vector(const MLPPCost::CostTypes cost) {
switch (cost) {
case COST_TYPE_MSE:
return &MLPPCost::mse_derivv;
case COST_TYPE_RMSE:
return &MLPPCost::rmse_derivv;
case COST_TYPE_MAE:
return &MLPPCost::mae_derivv;
case COST_TYPE_MBE:
return &MLPPCost::mbe_derivv;
case COST_TYPE_LOGISTIC_LOSS:
return &MLPPCost::log_loss_derivv;
case COST_TYPE_CROSS_ENTROPY:
return &MLPPCost::cross_entropy_derivv;
case COST_TYPE_HINGE_LOSS:
return &MLPPCost::hinge_loss_derivv;
case COST_TYPE_WASSERSTEIN_LOSS:
return &MLPPCost::wasserstein_loss_derivv;
default:
return NULL;
}
}
MLPPCost::MatrixDerivCostFunctionPointer MLPPCost::get_cost_function_ptr_deriv_matrix(const MLPPCost::CostTypes cost) {
switch (cost) {
case COST_TYPE_MSE:
return &MLPPCost::mse_derivm;
case COST_TYPE_RMSE:
return &MLPPCost::rmse_derivm;
case COST_TYPE_MAE:
return &MLPPCost::mae_derivm;
case COST_TYPE_MBE:
return &MLPPCost::mbe_derivm;
case COST_TYPE_LOGISTIC_LOSS:
return &MLPPCost::log_loss_derivm;
case COST_TYPE_CROSS_ENTROPY:
return &MLPPCost::cross_entropy_derivm;
case COST_TYPE_HINGE_LOSS:
return &MLPPCost::hinge_loss_derivm;
case COST_TYPE_WASSERSTEIN_LOSS:
return &MLPPCost::wasserstein_loss_derivm;
default:
return NULL;
}
}
real_t MLPPCost::run_cost_norm_vector(const CostTypes cost, const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y) {
switch (cost) {
case COST_TYPE_MSE:
return msev(y_hat, y);
case COST_TYPE_RMSE:
return rmsev(y_hat, y);
case COST_TYPE_MAE:
return maev(y_hat, y);
case COST_TYPE_MBE:
return mbev(y_hat, y);
case COST_TYPE_LOGISTIC_LOSS:
return log_lossv(y_hat, y);
case COST_TYPE_CROSS_ENTROPY:
return cross_entropyv(y_hat, y);
case COST_TYPE_HINGE_LOSS:
return hinge_lossv(y_hat, y);
case COST_TYPE_WASSERSTEIN_LOSS:
return wasserstein_lossv(y_hat, y);
default:
return 0;
}
}
real_t MLPPCost::run_cost_norm_matrix(const CostTypes cost, const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y) {
switch (cost) {
case COST_TYPE_MSE:
return msem(y_hat, y);
case COST_TYPE_RMSE:
return rmsem(y_hat, y);
case COST_TYPE_MAE:
return maem(y_hat, y);
case COST_TYPE_MBE:
return mbem(y_hat, y);
case COST_TYPE_LOGISTIC_LOSS:
return log_lossm(y_hat, y);
case COST_TYPE_CROSS_ENTROPY:
return cross_entropym(y_hat, y);
case COST_TYPE_HINGE_LOSS:
return hinge_lossm(y_hat, y);
case COST_TYPE_WASSERSTEIN_LOSS:
return wasserstein_lossm(y_hat, y);
default:
return 0;
}
}
Ref<MLPPVector> MLPPCost::run_cost_deriv_vector(const CostTypes cost, const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y) {
switch (cost) {
case COST_TYPE_MSE:
return mse_derivv(y_hat, y);
case COST_TYPE_RMSE:
return rmse_derivv(y_hat, y);
case COST_TYPE_MAE:
return mae_derivv(y_hat, y);
case COST_TYPE_MBE:
return mbe_derivv(y_hat, y);
case COST_TYPE_LOGISTIC_LOSS:
return log_loss_derivv(y_hat, y);
case COST_TYPE_CROSS_ENTROPY:
return cross_entropy_derivv(y_hat, y);
case COST_TYPE_HINGE_LOSS:
return hinge_loss_derivv(y_hat, y);
case COST_TYPE_WASSERSTEIN_LOSS:
return wasserstein_loss_derivv(y_hat, y);
default:
return Ref<MLPPVector>();
}
}
Ref<MLPPMatrix> MLPPCost::run_cost_deriv_matrix(const CostTypes cost, const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y) {
switch (cost) {
case COST_TYPE_MSE:
return mse_derivm(y_hat, y);
case COST_TYPE_RMSE:
return rmse_derivm(y_hat, y);
case COST_TYPE_MAE:
return mae_derivm(y_hat, y);
case COST_TYPE_MBE:
return mbe_derivm(y_hat, y);
case COST_TYPE_LOGISTIC_LOSS:
return log_loss_derivm(y_hat, y);
case COST_TYPE_CROSS_ENTROPY:
return cross_entropy_derivm(y_hat, y);
case COST_TYPE_HINGE_LOSS:
return hinge_loss_derivm(y_hat, y);
case COST_TYPE_WASSERSTEIN_LOSS:
return wasserstein_loss_derivm(y_hat, y);
default:
return Ref<MLPPMatrix>();
}
}
// ====== OLD ====== // ====== OLD ======
real_t MLPPCost::MSE(std::vector<real_t> y_hat, std::vector<real_t> y) { real_t MLPPCost::MSE(std::vector<real_t> y_hat, std::vector<real_t> y) {
@ -1044,4 +1224,19 @@ void MLPPCost::_bind_methods() {
ClassDB::bind_method(D_METHOD("dual_form_svm", "alpha", "X", "y"), &MLPPCost::dual_form_svm); ClassDB::bind_method(D_METHOD("dual_form_svm", "alpha", "X", "y"), &MLPPCost::dual_form_svm);
ClassDB::bind_method(D_METHOD("dual_form_svm_deriv", "alpha", "X", "y"), &MLPPCost::dual_form_svm_deriv); ClassDB::bind_method(D_METHOD("dual_form_svm_deriv", "alpha", "X", "y"), &MLPPCost::dual_form_svm_deriv);
ClassDB::bind_method(D_METHOD("run_cost_norm_vector", "cost", "y_hat", "y"), &MLPPCost::run_cost_norm_vector);
ClassDB::bind_method(D_METHOD("run_cost_norm_matrix", "cost", "y_hat", "y"), &MLPPCost::run_cost_norm_matrix);
ClassDB::bind_method(D_METHOD("run_cost_deriv_vector", "cost", "y_hat", "y"), &MLPPCost::run_cost_deriv_vector);
ClassDB::bind_method(D_METHOD("run_cost_deriv_matrix", "cost", "y_hat", "y"), &MLPPCost::run_cost_deriv_matrix);
BIND_ENUM_CONSTANT(COST_TYPE_MSE);
BIND_ENUM_CONSTANT(COST_TYPE_RMSE);
BIND_ENUM_CONSTANT(COST_TYPE_MAE);
BIND_ENUM_CONSTANT(COST_TYPE_MBE);
BIND_ENUM_CONSTANT(COST_TYPE_LOGISTIC_LOSS);
BIND_ENUM_CONSTANT(COST_TYPE_CROSS_ENTROPY);
BIND_ENUM_CONSTANT(COST_TYPE_HINGE_LOSS);
BIND_ENUM_CONSTANT(COST_TYPE_WASSERSTEIN_LOSS);
} }

32
mlpp/cost/cost.h
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@ -23,6 +23,18 @@
class MLPPCost : public Reference { class MLPPCost : public Reference {
GDCLASS(MLPPCost, Reference); GDCLASS(MLPPCost, Reference);
public:
enum CostTypes {
COST_TYPE_MSE = 0,
COST_TYPE_RMSE,
COST_TYPE_MAE,
COST_TYPE_MBE,
COST_TYPE_LOGISTIC_LOSS,
COST_TYPE_CROSS_ENTROPY,
COST_TYPE_HINGE_LOSS,
COST_TYPE_WASSERSTEIN_LOSS,
};
public: public:
real_t msev(const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y); real_t msev(const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y);
real_t msem(const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y); real_t msem(const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y);
@ -89,6 +101,24 @@ public:
Ref<MLPPVector> dual_form_svm_deriv(const Ref<MLPPVector> &alpha, const Ref<MLPPMatrix> &X, const Ref<MLPPVector> &y); Ref<MLPPVector> dual_form_svm_deriv(const Ref<MLPPVector> &alpha, const Ref<MLPPMatrix> &X, const Ref<MLPPVector> &y);
typedef real_t (MLPPCost::*VectorCostFunctionPointer)(const Ref<MLPPVector> &, const Ref<MLPPVector> &);
typedef real_t (MLPPCost::*MatrixCostFunctionPointer)(const Ref<MLPPMatrix> &, const Ref<MLPPMatrix> &);
typedef Ref<MLPPVector> (MLPPCost::*VectorDerivCostFunctionPointer)(const Ref<MLPPVector> &, const Ref<MLPPVector> &);
typedef Ref<MLPPMatrix> (MLPPCost::*MatrixDerivCostFunctionPointer)(const Ref<MLPPMatrix> &, const Ref<MLPPMatrix> &);
VectorCostFunctionPointer get_cost_function_ptr_normal_vector(const CostTypes cost);
MatrixCostFunctionPointer get_cost_function_ptr_normal_matrix(const CostTypes cost);
VectorDerivCostFunctionPointer get_cost_function_ptr_deriv_vector(const CostTypes cost);
MatrixDerivCostFunctionPointer get_cost_function_ptr_deriv_matrix(const CostTypes cost);
real_t run_cost_norm_vector(const CostTypes cost, const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y);
real_t run_cost_norm_matrix(const CostTypes cost, const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y);
Ref<MLPPVector> run_cost_deriv_vector(const CostTypes cost, const Ref<MLPPVector> &y_hat, const Ref<MLPPVector> &y);
Ref<MLPPMatrix> run_cost_deriv_matrix(const CostTypes cost, const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y);
// Regression Costs // Regression Costs
real_t MSE(std::vector<real_t> y_hat, std::vector<real_t> y); real_t MSE(std::vector<real_t> y_hat, std::vector<real_t> y);
real_t MSE(std::vector<std::vector<real_t>> y_hat, std::vector<std::vector<real_t>> y); real_t MSE(std::vector<std::vector<real_t>> y_hat, std::vector<std::vector<real_t>> y);
@ -159,4 +189,6 @@ protected:
static void _bind_methods(); static void _bind_methods();
}; };
VARIANT_ENUM_CAST(MLPPCost::CostTypes);
#endif /* Cost_hpp */ #endif /* Cost_hpp */