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Fixed warnings in ProbitReg.
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@ -14,7 +14,6 @@
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#include <iostream>
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#include <random>
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MLPPProbitReg::MLPPProbitReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg, real_t lambda, real_t alpha) :
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inputSet(inputSet), outputSet(outputSet), n(inputSet.size()), k(inputSet[0].size()), reg(reg), lambda(lambda), alpha(alpha) {
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y_hat.resize(n);
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@ -147,7 +146,9 @@ void MLPPProbitReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_siz
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// Creating the mini-batches
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int n_mini_batch = n / mini_batch_size;
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auto [inputMiniBatches, outputMiniBatches] = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch);
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auto createMiniBatchesResult = MLPPUtilities::createMiniBatches(inputSet, outputSet, n_mini_batch);
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auto inputMiniBatches = std::get<0>(createMiniBatchesResult);
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auto outputMiniBatches = std::get<1>(createMiniBatchesResult);
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// Creating the mini-batches
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for (int i = 0; i < n_mini_batch; i++) {
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@ -198,12 +199,12 @@ void MLPPProbitReg::MBGD(real_t learning_rate, int max_epoch, int mini_batch_siz
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}
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real_t MLPPProbitReg::score() {
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MLPPUtilities util;
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MLPPUtilities util;
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return util.performance(y_hat, outputSet);
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}
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void MLPPProbitReg::save(std::string fileName) {
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MLPPUtilities util;
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MLPPUtilities util;
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util.saveParameters(fileName, weights, bias);
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}
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@ -237,7 +238,6 @@ real_t MLPPProbitReg::propagate(std::vector<real_t> x) {
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// gaussianCDF ( wTx + b )
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void MLPPProbitReg::forwardPass() {
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MLPPLinAlg alg;
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MLPPActivation avn;
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z = propagate(inputSet);
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@ -13,8 +13,6 @@
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#include <string>
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#include <vector>
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class MLPPProbitReg {
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public:
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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);
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@ -52,5 +50,4 @@ private:
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real_t alpha; /* This is the controlling param for Elastic Net*/
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};
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#endif /* ProbitReg_hpp */
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