Smola's method should be complete.
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@@ -46,7 +46,11 @@ double SparseGreedyGprModel::PredictVariance(
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Vector kernel_values;
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ComputeKernelValues_(
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covariance, point_indices_in_dictionary, point, &kernel_values);
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Vector left_hand_side;
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SolveSystem_(dictionary_for_error_, kernel_values, &left_hand_side);
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double dot_product = la::Dot(left_hand_side, dot_product);
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double self_correlation = covariance.NormSq(point);
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return self_correlation - dot_product;
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}
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void SparseGreedyGprModel::FinalizeModel() {
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