用于司法文书分析的分类器的构建与评价
Construction and evaluation of classifiers for forensic document analysis
摘要：
在这项研究中，我们说明了一种统计方法，有疑问的文件检查。具体来说，我们考虑建设三个分类器，预测作者的样本文档的分类数据的基础上。为了评估这些分类器，我们使用一个数据集，其中包含大量的作家和每个作家少量的写作样本。由于所得到的分类器被发现有接近完美的精度使用留一交叉验证，我们提出了一种新的贝叶斯交叉验证方法来评估分类器。
英文摘要：
In this study we illustrate a statistical approach to questioned document examination. Specifically, we consider the construction of three classifiers that predict the writer of a sample document based on categorical data. To evaluate these classifiers, we use a data set with a large number of writers and a small number of writing samples per writer. Since the resulting classifiers were found to have near perfect accuracy using leave-one-out cross-validation, we propose a novel Bayesian-based cross-validation method for evaluating the classifiers.
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