rmontanana/BayesNet
rmontanana/BayesNet
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Remove unneeded output

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This commit is contained in:
Ricardo Montañana Gómez 2023-08-16 12:36:38 +02:00
parent 80b20f35b4
commit 918a7b4180
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
2 changed files with 0 additions and 3 deletions
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1
src/BayesNet/BayesMetrics.cc
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@ -45,7 +45,6 @@ namespace bayesnet {
auto mask = samples.index({ -1, "..." }) == value; auto mask = samples.index({ -1, "..." }) == value;
margin[value] = mask.sum().item<double>() / samples.size(1); margin[value] = mask.sum().item<double>() / samples.size(1);
} }
cout << "Margin: " << margin;
for (auto [first, second] : combinations) { for (auto [first, second] : combinations) {
int index_first = find(features.begin(), features.end(), first) - features.begin(); int index_first = find(features.begin(), features.end(), first) - features.begin();
int index_second = find(features.begin(), features.end(), second) - features.begin(); int index_second = find(features.begin(), features.end(), second) - features.begin();

2
src/BayesNet/TAN.cc
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@ -22,8 +22,6 @@ namespace bayesnet {
auto root = mi[mi.size() - 1].first; auto root = mi[mi.size() - 1].first;
// 2. Compute mutual information between each feature and the class // 2. Compute mutual information between each feature and the class
auto weights_matrix = metrics.conditionalEdge(weights); auto weights_matrix = metrics.conditionalEdge(weights);
cout << "*** Weights matrix ***\n";
cout << weights_matrix << "\n";
// 3. Compute the maximum spanning tree // 3. Compute the maximum spanning tree
auto mst = metrics.maximumSpanningTree(features, weights_matrix, root); auto mst = metrics.maximumSpanningTree(features, weights_matrix, root);
// 4. Add edges from the maximum spanning tree to the model // 4. Add edges from the maximum spanning tree to the model