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Add Models class

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This commit is contained in:
Ricardo Montañana Gómez
2023-07-28 12:11:52 +02:00
parent b420ad2bc2
commit 8049df436c
12 changed files with 85 additions and 35 deletions
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2
.vscode/launch.json vendored
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@@ -31,6 +31,8 @@
"--stratified",
"--title",
"Debug test",
"--seeds",
"1",
"-d",
"ionosphere"
],

2
sample/CMakeLists.txt
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@@ -3,5 +3,5 @@ include_directories(${BayesNet_SOURCE_DIR}/src/BayesNet)
include_directories(${BayesNet_SOURCE_DIR}/lib/Files)
include_directories(${BayesNet_SOURCE_DIR}/lib/mdlp)
include_directories(${BayesNet_SOURCE_DIR}/lib/argparse/include)
add_executable(BayesNetSample sample.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc)
add_executable(BayesNetSample sample.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc ${BayesNet_SOURCE_DIR}/src/Platform/Models.cc)
target_link_libraries(BayesNetSample BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}")

21
sample/sample.cc
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@@ -4,16 +4,11 @@
#include <thread>
#include <map>
#include <argparse/argparse.hpp>
#include "BaseClassifier.h"
#include "ArffFiles.h"
#include "Network.h"
#include "BayesMetrics.h"
#include "CPPFImdlp.h"
#include "KDB.h"
#include "SPODE.h"
#include "AODE.h"
#include "TAN.h"
#include "Folding.h"
#include "Models.h"
using namespace std;
@@ -91,13 +86,13 @@ int main(int argc, char** argv)
.default_value(string{ PATH }
);
program.add_argument("-m", "--model")
.help("Model to use {AODE, KDB, SPODE, TAN}")
.help("Model to use " + platform::Models::toString())
.action([](const std::string& value) {
static const vector<string> choices = { "AODE", "KDB", "SPODE", "TAN" };
static const vector<string> choices = platform::Models::getNames();
if (find(choices.begin(), choices.end(), value) != choices.end()) {
return value;
}
throw runtime_error("Model must be one of {AODE, KDB, SPODE, TAN}");
throw runtime_error("Model must be one of " + platform::Models::toString());
}
);
program.add_argument("--discretize").help("Discretize input dataset").default_value(false).implicit_value(true);
@@ -164,12 +159,8 @@ int main(int argc, char** argv)
states[feature] = vector<int>(maxes[feature]);
}
states[className] = vector<int>(maxes[className]);
auto classifiers = map<string, bayesnet::BaseClassifier*>({
{ "AODE", new bayesnet::AODE() }, { "KDB", new bayesnet::KDB(2) },
{ "SPODE", new bayesnet::SPODE(2) }, { "TAN", new bayesnet::TAN() }
}
);
bayesnet::BaseClassifier* clf = classifiers[model_name];
bayesnet::BaseClassifier* clf = platform::Models::get(model_name);
clf->fit(Xd, y, features, className, states);
auto score = clf->score(Xd, y);
auto lines = clf->show();

2
src/Platform/CMakeLists.txt
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@@ -4,5 +4,5 @@ include_directories(${BayesNet_SOURCE_DIR}/lib/Files)
include_directories(${BayesNet_SOURCE_DIR}/lib/mdlp)
include_directories(${BayesNet_SOURCE_DIR}/lib/argparse/include)
include_directories(${BayesNet_SOURCE_DIR}/lib/json/include)
add_executable(main main.cc Folding.cc platformUtils.cc Experiment.cc Datasets.cc CrossValidation.cc)
add_executable(main main.cc Folding.cc platformUtils.cc Experiment.cc Datasets.cc CrossValidation.cc Models.cc)
target_link_libraries(main BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}")

16
src/Platform/CrossValidation.cc
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@@ -1,8 +1,5 @@
#include "CrossValidation.h"
#include "AODE.h"
#include "TAN.h"
#include "KDB.h"
#include "SPODE.h"
#include "Models.h"
namespace platform {
using json = nlohmann::json;
@@ -10,10 +7,6 @@ namespace platform {
CrossValidation::CrossValidation(string modelName, bool stratified, int nfolds, vector<int> randomSeeds, platform::Datasets& datasets) : modelName(modelName), stratified(stratified), nfolds(nfolds), randomSeeds(randomSeeds), datasets(datasets)
{
classifiers = map<string, bayesnet::BaseClassifier*>({
{ "AODE", new bayesnet::AODE() }, { "KDB", new bayesnet::KDB(2) },
{ "SPODE", new bayesnet::SPODE(2) }, { "TAN", new bayesnet::TAN() }
});
}
Result CrossValidation::crossValidate(string fileName)
@@ -45,7 +38,7 @@ namespace platform {
fold = new KFold(nfolds, samples, seed);
cout << "Fold: " << flush;
for (int nfold = 0; nfold < nfolds; nfold++) {
bayesnet::BaseClassifier* model = classifiers[modelName];
bayesnet::BaseClassifier* model = Models::get(modelName);
result.setModelVersion(model->getVersion());
train_timer.start();
auto [train, test] = fold->getFold(nfold);
@@ -67,6 +60,11 @@ namespace platform {
test_time[item] = test_timer.getDuration();
accuracy_train[item] = accuracy_train_value;
accuracy_test[item] = accuracy_test_value;
// Store results and times in vector
result.addScoreTrain(accuracy_train_value);
result.addScoreTest(accuracy_test_value);
result.addTimeTrain(train_time[item].item<double>());
result.addTimeTest(test_time[item].item<double>());
item++;
}
delete fold;

2
src/Platform/CrossValidation.h
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@@ -5,7 +5,6 @@
#include <string>
#include <chrono>
#include "Folding.h"
#include "BaseClassifier.h"
#include "Datasets.h"
#include "Experiment.h"
@@ -17,7 +16,6 @@ namespace platform {
string modelName;
vector<int> randomSeeds;
platform::Datasets& datasets;
map<string, bayesnet::BaseClassifier*> classifiers;
public:
CrossValidation(string modelName, bool stratified, int nfolds, vector<int> randomSeeds, platform::Datasets& datasets);
~CrossValidation() = default;

1
src/Platform/Datasets.h
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@@ -60,6 +60,7 @@ namespace platform {
pair<torch::Tensor&, torch::Tensor&> getTensors(string name);
bool isDataset(string name);
};
vector<string> split(string, char);
};
#endif

4
src/Platform/Experiment.cc
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@@ -65,6 +65,10 @@ namespace platform {
j["test_time_std"] = r.getTestTimeStd();
j["time"] = r.getTestTime() + r.getTrainTime();
j["time_std"] = r.getTestTimeStd() + r.getTrainTimeStd();
j["scores_train"] = r.getScoresTrain();
j["scores_test"] = r.getScoresTest();
j["times_train"] = r.getTimesTrain();
j["times_test"] = r.getTimesTest();
j["nodes"] = r.getNodes();
j["leaves"] = r.getLeaves();
j["depth"] = r.getDepth();

9
src/Platform/Experiment.h
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@@ -27,6 +27,7 @@ namespace platform {
string dataset, hyperparameters, model_version;
int samples, features, classes;
double score_train, score_test, score_train_std, score_test_std, train_time, train_time_std, test_time, test_time_std;
vector<double> scores_train, scores_test, times_train, times_test;
float nodes, leaves, depth;
public:
Result() = default;
@@ -47,6 +48,10 @@ namespace platform {
Result& setLeaves(float leaves) { this->leaves = leaves; return *this; }
Result& setDepth(float depth) { this->depth = depth; return *this; }
Result& setModelVersion(string model_version) { this->model_version = model_version; return *this; }
Result& addScoreTrain(double score) { scores_train.push_back(score); return *this; }
Result& addScoreTest(double score) { scores_test.push_back(score); return *this; }
Result& addTimeTrain(double time) { times_train.push_back(time); return *this; }
Result& addTimeTest(double time) { times_test.push_back(time); return *this; }
const float get_score_train() const { return score_train; }
float get_score_test() { return score_test; }
const string& getDataset() const { return dataset; }
@@ -65,6 +70,10 @@ namespace platform {
const float getNodes() const { return nodes; }
const float getLeaves() const { return leaves; }
const float getDepth() const { return depth; }
const vector<double>& getScoresTrain() const { return scores_train; }
const vector<double>& getScoresTest() const { return scores_test; }
const vector<double>& getTimesTrain() const { return times_train; }
const vector<double>& getTimesTest() const { return times_test; }
const string& getModelVersion() const { return model_version; }
};
class Experiment {

8
src/Platform/Models.cc Normal file
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@@ -0,0 +1,8 @@
#include "Models.h"
namespace platform {
using namespace std;
map<string, bayesnet::BaseClassifier*> Models::classifiers = map<string, bayesnet::BaseClassifier*>({
{ "AODE", new bayesnet::AODE() }, { "KDB", new bayesnet::KDB(2) },
{ "SPODE", new bayesnet::SPODE(2) }, { "TAN", new bayesnet::TAN() }
});
}

33
src/Platform/Models.h Normal file
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@@ -0,0 +1,33 @@
#ifndef MODELS_H
#define MODELS_H
#include <map>
#include "BaseClassifier.h"
#include "AODE.h"
#include "TAN.h"
#include "KDB.h"
#include "SPODE.h"
namespace platform {
class Models {
private:
static map<string, bayesnet::BaseClassifier*> classifiers;
public:
static bayesnet::BaseClassifier* get(string name) { return classifiers[name]; }
static vector<string> getNames()
{
vector<string> names;
for (auto& [name, classifier] : classifiers) {
names.push_back(name);
}
return names;
}
static string toString()
{
string names = "";
for (auto& [name, classifier] : classifiers) {
names += name + ", ";
}
return "{" + names.substr(0, names.size() - 2) + "}";
}
};
}
#endif

20
src/Platform/main.cc
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@@ -5,6 +5,7 @@
#include "Datasets.h"
#include "DotEnv.h"
#include "CrossValidation.h"
#include "Models.h"
using namespace std;
@@ -21,16 +22,16 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
.default_value(string{ PATH_DATASETS }
);
program.add_argument("-m", "--model")
.help("Model to use {AODE, KDB, SPODE, TAN}")
.help("Model to use " + platform::Models::toString())
.action([](const std::string& value) {
static const vector<string> choices = { "AODE", "KDB", "SPODE", "TAN" };
static const vector<string> choices = platform::Models::getNames();
if (find(choices.begin(), choices.end(), value) != choices.end()) {
return value;
}
throw runtime_error("Model must be one of {AODE, KDB, SPODE, TAN}");
throw runtime_error("Model must be one of " + platform::Models::toString());
}
);
program.add_argument("--title").required().help("Experiment title");
program.add_argument("--title").default_value("").help("Experiment title");
program.add_argument("--discretize").help("Discretize input dataset").default_value((bool)stoi(env.get("discretize"))).implicit_value(true);
program.add_argument("--stratified").help("If Stratified KFold is to be done").default_value((bool)stoi(env.get("stratified"))).implicit_value(true);
program.add_argument("-f", "--folds").help("Number of folds").default_value(stoi(env.get("n_folds"))).scan<'i', int>().action([](const string& value) {
@@ -47,9 +48,8 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
catch (...) {
throw runtime_error("Number of folds must be an integer");
}});
auto seed_values = env.getSeeds();
program.add_argument("-s", "--seeds").help("Random seeds comma separated. Set to -1 to have pseudo random").default_value(seed_values);
program.add_argument("-s", "--seeds").nargs(1, 10).help("Random seeds. Set to -1 to have pseudo random").scan<'i', int>().default_value(seed_values);
bool class_last, discretize_dataset, stratified;
int n_folds;
vector<int> seeds;
@@ -66,6 +66,9 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
complete_file_name = path + file_name + ".arff";
class_last = false;//datasets[file_name];
title = program.get<string>("title");
if (title == "" && file_name == "") {
throw runtime_error("title is mandatory if dataset is not provided");
}
}
catch (const exception& err) {
cerr << err.what() << endl;
@@ -89,17 +92,20 @@ int main(int argc, char** argv)
auto seeds = program.get<vector<int>>("seeds");
vector<string> filesToProcess;
auto datasets = platform::Datasets(path, true, platform::ARFF);
auto title = program.get<string>("title");
if (file_name != "") {
if (!datasets.isDataset(file_name)) {
cerr << "Dataset " << file_name << " not found" << endl;
exit(1);
}
if (title == "") {
title = "Test " + file_name + " " + model_name + " " + to_string(n_folds) + " folds";
}
filesToProcess.push_back(file_name);
} else {
filesToProcess = platform::Datasets(path, true, platform::ARFF).getNames();
saveResults = true; // Only save results if all datasets are processed
}
auto title = program.get<string>("title");
/*
* Begin Processing