rmontanana/BayesNet
1
0
Fork 0
Code Issues 2 Pull Requests 1 Actions Packages Projects Releases 6 Wiki Activity

Refactor hyperparameters classifier management

Browse Source
This commit is contained in:
Ricardo Montañana Gómez
2024-04-08 00:55:30 +02:00
parent 0d6a081d01
commit 9014649a0d
8 changed files with 43 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
bayesnet/classifiers/Classifier.cc
View File

@@ -1,3 +1,4 @@
#include <sstream>
#include "bayesnet/utils/bayesnetUtils.h"
#include "Classifier.h"
@@ -27,10 +28,11 @@ namespace bayesnet {
dataset = torch::cat({ dataset, yresized }, 0);
}
catch (const std::exception& e) {
std::cerr << e.what() << '\n';
std::cout << "X dimensions: " << dataset.sizes() << "\n";
std::cout << "y dimensions: " << ytmp.sizes() << "\n";
exit(1);
std::stringstream oss;
oss << "* Error in X and y dimensions *\n";
oss << "X dimensions: " << dataset.sizes() << "\n";
oss << "y dimensions: " << ytmp.sizes();
throw std::runtime_error(oss.str());
}
}
void Classifier::trainModel(const torch::Tensor& weights)
@@ -179,6 +181,8 @@ namespace bayesnet {
}
void Classifier::setHyperparameters(const nlohmann::json& hyperparameters)
{
//For classifiers that don't have hyperparameters
if (!hyperparameters.empty()) {
throw std::invalid_argument("Invalid hyperparameters" + hyperparameters.dump());
}
}
}

6
bayesnet/classifiers/KDB.cc
View File

@@ -6,14 +6,18 @@ namespace bayesnet {
validHyperparameters = { "k", "theta" };
}
void KDB::setHyperparameters(const nlohmann::json& hyperparameters)
void KDB::setHyperparameters(const nlohmann::json& hyperparameters_)
{
auto hyperparameters = hyperparameters_;
if (hyperparameters.contains("k")) {
k = hyperparameters["k"];
hyperparameters.erase("k");
}
if (hyperparameters.contains("theta")) {
theta = hyperparameters["theta"];
hyperparameters.erase("theta");
}
Classifier::setHyperparameters(hyperparameters);
}
void KDB::buildModel(const torch::Tensor& weights)
{

2
bayesnet/classifiers/KDB.h
View File

@@ -14,7 +14,7 @@ namespace bayesnet {
public:
explicit KDB(int k, float theta = 0.03);
virtual ~KDB() = default;
void setHyperparameters(const nlohmann::json& hyperparameters) override;
void setHyperparameters(const nlohmann::json& hyperparameters_) override;
std::vector<std::string> graph(const std::string& name = "KDB") const override;
};
}

4
bayesnet/ensembles/AODE.cc
View File

@@ -13,9 +13,7 @@ namespace bayesnet {
predict_voting = hyperparameters["predict_voting"];
hyperparameters.erase("predict_voting");
}
if (!hyperparameters.empty()) {
throw std::invalid_argument("Invalid hyperparameters" + hyperparameters.dump());
}
Classifier::setHyperparameters(hyperparameters);
}
void AODE::buildModel(const torch::Tensor& weights)
{

4
bayesnet/ensembles/BoostAODE.cc
View File

@@ -94,9 +94,7 @@ namespace bayesnet {
}
hyperparameters.erase("select_features");
}
if (!hyperparameters.empty()) {
throw std::invalid_argument("Invalid hyperparameters" + hyperparameters.dump());
}
Classifier::setHyperparameters(hyperparameters);
}
std::tuple<torch::Tensor&, double, bool> update_weights(torch::Tensor& ytrain, torch::Tensor& ypred, torch::Tensor& weights)
{

2
bayesnet/ensembles/BoostAODE.h
View File

@@ -20,7 +20,7 @@ namespace bayesnet {
BoostAODE(bool predict_voting = false);
virtual ~BoostAODE() = default;
std::vector<std::string> graph(const std::string& title = "BoostAODE") const override;
void setHyperparameters(const nlohmann::json& hyperparameters) override;
void setHyperparameters(const nlohmann::json& hyperparameters_) override;
protected:
void buildModel(const torch::Tensor& weights) override;
void trainModel(const torch::Tensor& weights) override;