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Added logit activation

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This commit is contained in:
novak_99 2021-09-24 21:00:04 -07:00
parent d47cd7e976
commit 51ec771789
7 changed files with 56 additions and 22 deletions
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21
MLPP/Activation/Activation.cpp
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@ -218,6 +218,27 @@ namespace MLPP{
return alg.scalarMultiply(-1, alg.scalarAdd(-1, alg.exp(alg.scalarMultiply(-1, alg.exp(z)))));
}
double Activation::logit(double z, bool deriv){
if(deriv) { return 1/z - 1/(z-1); }
return std::log(z / (1 + z));
}
std::vector<double> Activation::logit(std::vector<double> z, bool deriv){
LinAlg alg;
if(deriv) {
return alg.subtraction(alg.elementWiseDivision(alg.onevec(z.size()), z), alg.elementWiseDivision(alg.onevec(z.size()), alg.subtraction(z, alg.onevec(z.size()))));
}
return alg.log(alg.elementWiseDivision(z, alg.subtraction(alg.onevec(z.size()), z)));
}
std::vector<std::vector<double>> Activation::logit(std::vector<std::vector<double>> z, bool deriv){
LinAlg alg;
if(deriv) {
return alg.subtraction(alg.elementWiseDivision(alg.onemat(z.size(), z[0].size()), z), alg.elementWiseDivision(alg.onemat(z.size(), z[0].size()), alg.subtraction(z, alg.onemat(z.size(), z[0].size()))));
}
return alg.log(alg.elementWiseDivision(z, alg.subtraction(alg.onemat(z.size(), z[0].size()), z)));
}
double Activation::unitStep(double z, bool deriv){
if(deriv) {
return 0;

4
MLPP/Activation/Activation.hpp
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@ -45,6 +45,10 @@ namespace MLPP{
std::vector<double> cloglog(std::vector<double> z, bool deriv = 0);
std::vector<std::vector<double>> cloglog(std::vector<std::vector<double>> z, bool deriv = 0);
double logit(double z, bool deriv = 0);
std::vector<double> logit(std::vector<double> z, bool deriv = 0);
std::vector<std::vector<double>> logit(std::vector<std::vector<double>> z, bool deriv = 0);
double unitStep(double z, bool deriv = 0);
std::vector<double> unitStep(std::vector<double> z, bool deriv = 0);
std::vector<std::vector<double>> unitStep(std::vector<std::vector<double>> z, bool deriv = 0);

7
MLPP/HiddenLayer/HiddenLayer.cpp
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@ -43,6 +43,9 @@ namespace MLPP {
activation_map["CLogLog"] = &Activation::cloglog;
activationTest_map["CLogLog"] = &Activation::cloglog;
activation_map["Logit"] = &Activation::logit;
activationTest_map["Logit"] = &Activation::logit;
activation_map["GaussianCDF"] = &Activation::gaussianCDF;
activationTest_map["GaussianCDF"] = &Activation::gaussianCDF;
@ -52,8 +55,8 @@ namespace MLPP {
activation_map["GELU"] = &Activation::GELU;
activationTest_map["GELU"] = &Activation::GELU;
activation_map["Sign"] = &Activation::unitStep;
activationTest_map["Sign"] = &Activation::unitStep;
activation_map["Sign"] = &Activation::sign;
activationTest_map["Sign"] = &Activation::sign;
activation_map["UnitStep"] = &Activation::unitStep;
activationTest_map["UnitStep"] = &Activation::unitStep;

7
MLPP/MultiOutputLayer/MultiOutputLayer.cpp
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@ -45,6 +45,9 @@ namespace MLPP {
activation_map["CLogLog"] = &Activation::cloglog;
activationTest_map["CLogLog"] = &Activation::cloglog;
activation_map["Logit"] = &Activation::logit;
activationTest_map["Logit"] = &Activation::logit;
activation_map["GaussianCDF"] = &Activation::gaussianCDF;
activationTest_map["GaussianCDF"] = &Activation::gaussianCDF;
@ -54,8 +57,8 @@ namespace MLPP {
activation_map["GELU"] = &Activation::GELU;
activationTest_map["GELU"] = &Activation::GELU;
activation_map["Sign"] = &Activation::unitStep;
activationTest_map["Sign"] = &Activation::unitStep;
activation_map["Sign"] = &Activation::sign;
activationTest_map["Sign"] = &Activation::sign;
activation_map["UnitStep"] = &Activation::unitStep;
activationTest_map["UnitStep"] = &Activation::unitStep;

7
MLPP/OutputLayer/OutputLayer.cpp
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@ -42,6 +42,9 @@ namespace MLPP {
activation_map["CLogLog"] = &Activation::cloglog;
activationTest_map["CLogLog"] = &Activation::cloglog;
activation_map["Logit"] = &Activation::logit;
activationTest_map["Logit"] = &Activation::logit;
activation_map["GaussianCDF"] = &Activation::gaussianCDF;
activationTest_map["GaussianCDF"] = &Activation::gaussianCDF;
@ -51,8 +54,8 @@ namespace MLPP {
activation_map["GELU"] = &Activation::GELU;
activationTest_map["GELU"] = &Activation::GELU;
activation_map["Sign"] = &Activation::unitStep;
activationTest_map["Sign"] = &Activation::unitStep;
activation_map["Sign"] = &Activation::sign;
activationTest_map["Sign"] = &Activation::sign;
activation_map["UnitStep"] = &Activation::unitStep;
activationTest_map["UnitStep"] = &Activation::unitStep;

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32
main.cpp
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@ -197,14 +197,14 @@ int main() {
// data.setData(4, "/Users/marcmelikyan/Desktop/Data/Iris.csv", inputSet, tempOutputSet);
// std::vector<std::vector<double>> outputSet = data.oneHotRep(tempOutputSet, 3);
// SUPPORT VECTOR CLASSIFICATION
std::vector<std::vector<double>> inputSet;
std::vector<double> outputSet;
data.setData(30, "/Users/marcmelikyan/Desktop/Data/BreastCancerSVM.csv", inputSet, outputSet);
SVC model(inputSet, outputSet, 1);
model.SGD(0.00001, 100000, 1);
alg.printVector(model.modelSetTest(inputSet));
std::cout << "ACCURACY: " << 100 * model.score() << "%" << std::endl;
// // SUPPORT VECTOR CLASSIFICATION
// std::vector<std::vector<double>> inputSet;
// std::vector<double> outputSet;
// data.setData(30, "/Users/marcmelikyan/Desktop/Data/BreastCancerSVM.csv", inputSet, outputSet);
// SVC model(inputSet, outputSet, 1);
// model.SGD(0.00001, 100000, 1);
// alg.printVector(model.modelSetTest(inputSet));
// std::cout << "ACCURACY: " << 100 * model.score() << "%" << std::endl;
// SoftmaxReg model(inputSet, outputSet);
// model.SGD(0.001, 20000, 0);
@ -404,16 +404,16 @@ int main() {
// // Testing new Functions
// double z_s = 0.001;
// std::cout << avn.sinc(z_s) << std::endl;
// std::cout << avn.sinc(z_s, 1) << std::endl;
// std::cout << avn.logit(z_s) << std::endl;
// std::cout << avn.logit(z_s, 1) << std::endl;
// std::vector<double> z_v = {0.001, 5};
// alg.printVector(avn.sinc(z_v));
// alg.printVector(avn.sinc(z_v, 1));
// std::vector<double> z_v = {0.001};
// alg.printVector(avn.logit(z_v));
// alg.printVector(avn.logit(z_v, 1));
// std::vector<std::vector<double>> Z_m = {{0.001, 5}};
// alg.printMatrix(avn.sinc(Z_m));
// alg.printMatrix(avn.sinc(Z_m, 1));
// std::vector<std::vector<double>> Z_m = {{0.001}};
// alg.printMatrix(avn.logit(Z_m));
// alg.printMatrix(avn.logit(Z_m, 1));
// std::cout << alg.trace({{1,2}, {3,4}}) << std::endl;
// alg.printMatrix(alg.pinverse({{1,2}, {3,4}}));