Mathematical Sciences: Statistical Theory for Classification

概率模型可以用来自然地区分 即使这些观测结果 都是混合在一起的，没有标签 既定理论借鉴了 混合模型，模态模型，以及，对于进化 分类，广义马尔可夫模型。 本研究 介绍并研究了一类新的概率模型： 产品划分模型 这些将在以下方面得到广泛应用： 确定分类和基于部分或 完整的分类。 这些分类的应用 算法包括进化树的构建， 模拟过程的变点识别、图像 重建和故障预测的复杂情况下， 航天飞机

Probability models can be used to distinguish naturally occurring clusters of observations even when these observations are intermixed and unlabelled. Established theory draws on mixture models, modal models, and, for evolutionary classification, generalized Markov models. This research introduces and investigates a new class of probability models: product partition models. These will have wide application in determining classifications and in predicting based on partial or complete classifications. Applications for these classification algorithms include the construction of evolutionary trees, recognition of change-points for modelled processes, image reconstruction, and failure prediction for complex cases like the space shuttle.