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CatagoricalCrossentrophy
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Fixed the loss functions for categories and is ready for accuracy calculation on page 129
This commit is contained in:
Michelle
2025-10-07 13:09:25 +02:00
parent 8e70310760
commit 66b3a4ee6b
34 changed files with 754 additions and 260 deletions
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include/modules/neural_networks/datasets/spiral.h
+4 -4
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@@ -11,7 +11,7 @@
namespace neural_networks{
template <typename TX, typename Ty>
void create_spital_data(const uint64_t samples, const uint64_t classes, utils::Matrix<TX>& X, utils::Vector<Ty>& y) {
void create_spital_data(const uint64_t samples, const uint64_t classes, utils::Matrix<TX>& X, utils::Matrix<Ty>& y) {
const uint64_t rows = samples*classes;
TX r, t;
@@ -21,8 +21,8 @@ namespace neural_networks{
if ((rows != X.rows()) || (X.cols() != 2)){
X.resize(samples*classes, 2);
}
if (rows != y.size()){
y.resize(rows);
if (rows != y.rows()){
y.resize(rows, 1);
}
for (uint64_t i = 0; i < classes; ++i){
@@ -33,7 +33,7 @@ namespace neural_networks{
X(row_idx, 0) = r*std::cos(t*2.5) + utils::random(TX{-0.15}, TX{0.15});
X(row_idx, 1) = r*std::sin(t*2.5) + utils::random(TX{-0.15}, TX{0.15});
y[row_idx] = static_cast<Ty>(i);
y(row_idx, 0) = static_cast<Ty>(i);
}
}
}