摘要: Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the learning process, but in relational domains, the inf... 展开
作者 | Neville, J. Jensen, D. | ||
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原报告号 | ADA474037 | 总页数 | 13 |
报告类别/文献类型 | AD / NTIS科技报告 | ||
关键词 | Statistical inference Algorithms Symposia Adaptive systems Variational methods Bias Errors Models |