Set intolerant convergence
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@ -108,8 +108,10 @@ namespace bayesnet {
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void BoostAODE::trainModel(const torch::Tensor& weights)
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{
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std::unordered_set<int> featuresUsed;
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int tolerance = 5; // number of times the accuracy can be lower than the threshold
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if (selectFeatures) {
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featuresUsed = initializeModels();
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tolerance = 0; // Remove tolerance if features are selected
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}
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if (maxModels == 0)
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maxModels = .1 * n > 10 ? .1 * n : n;
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@ -119,7 +121,6 @@ namespace bayesnet {
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double priorAccuracy = 0.0;
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double delta = 1.0;
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double threshold = 1e-4;
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int tolerance = 5; // number of times the accuracy can be lower than the threshold
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int count = 0; // number of times the accuracy is lower than the threshold
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fitted = true; // to enable predict
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// Step 0: Set the finish condition
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