AI 中文总结
本文提出Seer系统，通过生成分类学习性能观测数据并构建最大似然统计模型，预测达到目标性能所需的训练样本数及最大准确率，并在三个真实领域实验中验证其有效性。
AI 中文摘要
本文的研究聚焦于机器学习性能的建模。论文介绍了Seer系统，该系统生成分类学习性能的经验观测数据，并利用这些观测数据创建统计模型。这些模型可用于预测达到期望性能水平所需的训练样本数量，以及在训练样本无限多的情况下可能达到的最大准确率。Seer通过以下三点推进了现有技术水平：1）模型体现了分类学习的最佳约束和最有用的参数；2）算法能够高效地找到最大似然模型；3）在来自三个领域的真实数据上展示了此类建模的实际应用。论文的第一部分概述了良好的分类学习性能最大似然模型所需满足的要求。接下来，探讨了此类模型的合理设计选择。在这些模型之间进行选择是一个非线性规划问题，但通过利用适当的问题约束，该任务被简化为一个非线性回归任务，可以通过高效的迭代算法求解。论文的后半部分描述了在大豆病害、心脏病和听觉问题领域进行的近100项实验。测试表明，Seer在刻画学习性能方面表现出色，并且在预测学习性能方面似乎已达到尽可能好的水平。最后，提出了针对特定情况选择回归模型的建议，并指出了进一步研究的方向。
英文摘要
The research presented here focuses on modeling machine-learning performance. The thesis introduces Seer, a system that generates empirical observations of classification-learning performance and then uses those observations to create statistical models. The models can be used to predict the number of training examples needed to achieve a desired level and the maximum accuracy possible given an unlimited number of training examples. Seer advances the state of the art with 1) models that embody the best constraints for classification learning and most useful parameters, 2) algorithms that efficiently find maximum-likelihood models, and 3) a demonstration on real-world data from three domains of a practicable application of such modeling. The first part of the thesis gives an overview of the requirements for a good maximum-likelihood model of classification-learning performance. Next, reasonable design choices for such models are explored. Selection among such models is a task of nonlinear programming, but by exploiting appropriate problem constraints, the task is reduced to a nonlinear regression task that can be solved with an efficient iterative algorithm. The latter part of the thesis describes almost 100 experiments in the domains of soybean disease, heart disease, and audiological problems. The tests show that Seer is excellent at characterizing learning-performance and that it seems to be as good as possible at predicting learning performance. Finally, recommendations for choosing a regression model for a particular situation are made and directions for further research are identified.
Comments104 pages. Ph.D. dissertation, Department of Computer Science, University of Illinois at Urbana-Champaign, 1995. Original dissertation deposited in arXiv in 2026
