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DISCRIMINATIVE FEATURE SELECTION FOR DATA SEQUENCES

机译:数据序列的区别性特征选择

摘要

A discriminative feature selection method for selecting a set of features from a set of training data sequences is described. The training data sequences are generated by at least two data sources, and each data sequence consists of a sequence of data symbols taken from an alphabet. The method is performed by first building a suffix tree from the training data. The suffix tree contains only suffixes of the data sequences having an empirical probability of occurrence greater than a first predetermined threshold, from at least one of the sources. Next the suffix tree is pruned of all suffixes for which there exists in the suffix tree a shorter suffix having equivalent predictive capability, for all of the data sources.
机译:描述了一种用于从一组训练数据序列中选择一组特征的区分特征选择方法。训练数据序列由至少两个数据源生成,并且每个数据序列由从字母表中提取的一系列数据符号组成。通过首先根据训练数据构建后缀树来执行该方法。后缀树仅包含来自至少一个源的数据序列的后缀,该数据序列的后缀的经验发生概率大于第一预定阈值。接下来,对所有后缀中的后缀树进行修剪,对于所有数据源,在后缀树中存在一个较短的后缀,该后缀具有等效的预测能力。

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