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Fixed warnings in SoftMaxReg.

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Relintai 2023-02-10 14:15:49 +01:00
parent da6324830d
commit 1e2078f428
2 changed files with 5 additions and 7 deletions
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9
mlpp/softmax_reg/softmax_reg.cpp
View File

@ -14,7 +14,6 @@
#include <iostream>
#include <random>
MLPPSoftmaxReg::MLPPSoftmaxReg(std::vector<std::vector<real_t>> inputSet, std::vector<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()), n_class(outputSet[0].size()), reg(reg), lambda(lambda), alpha(alpha) {
y_hat.resize(n);
@ -120,7 +119,9 @@ void MLPPSoftmaxReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_si
// Creating the mini-batches
int n_mini_batch = n / mini_batch_size;
auto [inputMiniBatches, outputMiniBatches] = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch);
auto batches = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch);
auto inputMiniBatches = std::get<0>(batches);
auto outputMiniBatches = std::get<1>(batches);
while (true) {
for (int i = 0; i < n_mini_batch; i++) {
@ -154,12 +155,12 @@ void MLPPSoftmaxReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_si
}
real_t MLPPSoftmaxReg::score() {
MLPPUtilities util;
MLPPUtilities util;
return util.performance(y_hat, outputSet);
}
void MLPPSoftmaxReg::save(std::string fileName) {
MLPPUtilities util;
MLPPUtilities util;
util.saveParameters(fileName, weights, bias);
}

3
mlpp/softmax_reg/softmax_reg.h
View File

@ -13,8 +13,6 @@
#include <string>
#include <vector>
class MLPPSoftmaxReg {
public:
MLPPSoftmaxReg(std::vector<std::vector<real_t>> inputSet, std::vector<std::vector<real_t>> outputSet, std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
@ -49,5 +47,4 @@ private:
real_t alpha; /* This is the controlling param for Elastic Net*/
};
#endif /* SoftmaxReg_hpp */