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Adding a clusterer on top of the network

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This commit is contained in:
emeric
2018-12-10 13:02:44 +01:00
parent 63abdc782c
commit de712936eb
2 changed files with 165 additions and 53 deletions
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tools/classifier/LmsClassifier.cpp
+16 -53
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@@ -6,9 +6,11 @@
#include "classifier/SOM.hpp"
#include "classifier/DataNormalizer.hpp"
#include "classifier/Clusterer.hpp"
int main(int argc, char *argv[])
{
if (argc != 2)
{
std::cerr << "Usage: <file>" << std::endl;
@@ -17,64 +19,25 @@ int main(int argc, char *argv[])
auto iterationCount = std::stoul(argv[1]);
using namespace SOM;
SOM::Network network(5, 5, 2);
network.dump(std::cout);
std::vector< std::vector<double> > inputValues =
std::vector< std::pair<std::vector<SOM::InputVector::value_type>, std::string> > inputValues =
{
{ 160, 1 },
{ 80, -1 },
{ 80, -0.75 },
{ 240, 0.5 },
{ 240, -0.5 },
{ 120, -0.5 },
{ 140, -0.5 },
{{ 160, 1 }, { "banane" }},
{{ 80, -1 }, { "poire" }},
{{ 80, -0.75 }, {"pocolat"}},
{{ 240, 0.5 }, {"abricot"}},
{{ 240, -0.5 }, {"peche"}},
{{ 120, -0.5 }, {"fraise"}},
{{ 140, -0.5 }, {"myrtille"}},
};
std::cout << "Before normalization:" << std::endl;
for (const auto& inputValue : inputValues)
{
std::cout << inputValue << std::endl;
}
std::cout << std::endl;
Clusterer<std::string> classifier(inputValues, 2, iterationCount);
std::cout << "After normalization:" << std::endl;
std::cout << "Clusterer :" << std::endl;
classifier.dump(std::cout);
SOM::DataNormalizer normalizer(2);
normalizer.computeNormalizationFactors(inputValues);
for (auto& inputValue : inputValues)
normalizer.normalizeData(inputValue);
for (const auto& inputValue : inputValues)
{
std::cout << inputValue << std::endl;
}
std::cout << std::endl;
for (const auto& inputValue : inputValues)
{
auto res = network.classify(inputValue);
std::cout << "Found at " << res.x << ", " << res.y << std::endl;
}
std::cout << "Training network for " << iterationCount << " iterations" << std::endl;
network.train(inputValues, iterationCount);
network.dump(std::cout);
std::cout << "OK" << std::endl;
for (const auto& inputValue : inputValues)
{
auto res = network.classify(inputValue);
std::cout << "Found at " << res.x << ", " << res.y << std::endl;
}
std::cout << "Classify 195, 0.35 = " << std::endl;
for (const auto& val : classifier.getClusterValues({195, 0.35}))
std::cout << val << " " << std::endl;
return EXIT_SUCCESS;
}