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@ -80,9 +80,9 @@ namespace MLPP{
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double y_hat = Evaluate(inputSet[outputIndex]);
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double y_hat = Evaluate(inputSet[outputIndex]);
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double z = propagate(inputSet[outputIndex]);
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double z = propagate(inputSet[outputIndex]);
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cost_prev = Cost(std::vector<double>({z}), std::vector<double>({outputSet[outputIndex]}), weights, C);
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cost_prev = Cost({z}, {outputSet[outputIndex]}, weights, C);
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double costDeriv = cost.HingeLossDeriv({z}, {outputSet[outputIndex]}, C)[0];
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double costDeriv = cost.HingeLossDeriv(std::vector<double>({z}), std::vector<double>({outputSet[outputIndex]}), C)[0]; // Explicit conversion to avoid ambiguity with overloaded function. Error occured on Ubuntu.
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// Weight Updation
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// Weight Updation
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weights = alg.subtraction(weights, alg.scalarMultiply(learning_rate * costDeriv, inputSet[outputIndex]));
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weights = alg.subtraction(weights, alg.scalarMultiply(learning_rate * costDeriv, inputSet[outputIndex]));
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