This article considers a semi-supervised classification setting on a Gaussian mixture model, where the data is not labeled strictly as usual, but instead with uncertain labels. Our main aim is to compute the Bayes risk for this model. We compare the behavior of the Bayes risk and the best known algorithm for this model. This comparison eventually gives new insights over the algorithm.

翻译：本文考虑高斯混合模型下的半监督分类设置，其中数据并非如常规被严格标注，而是带有不确定性标注。我们的主要目标是计算该模型的贝叶斯风险。我们将贝叶斯风险与该模型下已知最优算法的行为进行比较，这一比较最终为算法提供了新的见解。