Relintai/pmlpp
1
0
Fork 0
mirror of https://github.com/Relintai/pmlpp.git synced 2024-12-22 15:06:47 +01:00
Code Issues Packages Projects Releases Wiki Activity

Fixed warnings in ProbitReg.

Browse Source
This commit is contained in:
Relintai 2023-02-09 16:42:46 +01:00
parent d341f6f8d0
commit 0289fcb70e
2 changed files with 5 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
mlpp/probit_reg/probit_reg.cpp
View File

@ -14,7 +14,6 @@
#include <iostream> #include <iostream>
#include <random> #include <random>
MLPPProbitReg::MLPPProbitReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg, real_t lambda, real_t alpha) : MLPPProbitReg::MLPPProbitReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg, real_t lambda, real_t alpha) :
inputSet(inputSet), outputSet(outputSet), n(inputSet.size()), k(inputSet[0].size()), reg(reg), lambda(lambda), alpha(alpha) { inputSet(inputSet), outputSet(outputSet), n(inputSet.size()), k(inputSet[0].size()), reg(reg), lambda(lambda), alpha(alpha) {
y_hat.resize(n); y_hat.resize(n);
@ -147,7 +146,9 @@ void MLPPProbitReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_siz
// Creating the mini-batches // Creating the mini-batches
int n_mini_batch = n / mini_batch_size; int n_mini_batch = n / mini_batch_size;
auto [inputMiniBatches, outputMiniBatches] = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch); auto createMiniBatchesResult = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch);
auto inputMiniBatches = std::get<0>(createMiniBatchesResult);
auto outputMiniBatches = std::get<1>(createMiniBatchesResult);
// Creating the mini-batches // Creating the mini-batches
for (int i = 0; i < n_mini_batch; i++) { for (int i = 0; i < n_mini_batch; i++) {
@ -198,12 +199,12 @@ void MLPPProbitReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_siz
} }
real_t MLPPProbitReg::score() { real_t MLPPProbitReg::score() {
MLPPUtilities util; MLPPUtilities util;
return util.performance(y_hat, outputSet); return util.performance(y_hat, outputSet);
} }
void MLPPProbitReg::save(std::string fileName) { void MLPPProbitReg::save(std::string fileName) {
MLPPUtilities util; MLPPUtilities util;
util.saveParameters(fileName, weights, bias); util.saveParameters(fileName, weights, bias);
} }
@ -237,7 +238,6 @@ real_t MLPPProbitReg::propagate(std::vector<real_t> x) {
// gaussianCDF ( wTx + b ) // gaussianCDF ( wTx + b )
void MLPPProbitReg::forwardPass() { void MLPPProbitReg::forwardPass() {
MLPPLinAlg alg;
MLPPActivation avn; MLPPActivation avn;
z = propagate(inputSet); z = propagate(inputSet);

3
mlpp/probit_reg/probit_reg.h
View File

@ -13,8 +13,6 @@
#include <string> #include <string>
#include <vector> #include <vector>
class MLPPProbitReg { class MLPPProbitReg {
public: public:
MLPPProbitReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5); MLPPProbitReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
@ -52,5 +50,4 @@ private:
real_t alpha; /* This is the controlling param for Elastic Net*/ real_t alpha; /* This is the controlling param for Elastic Net*/
}; };
#endif /* ProbitReg_hpp */ #endif /* ProbitReg_hpp */