Interpretable Predictive Results in Classification of Waka Poets

Aiha Ikegami, T. Nakanishi
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Abstract

In this paper, we present our proposed method for providing interpretable predictive results in the classification of waka poets. Waka is a type of traditional Japanese poetry. Waka poetry reflects the mind of waka poets. By extracting taste and feeling from waka poetry, it is possible to reveal aesthetic notions in waka poets. This work focuses on waka poetry composed by the Sanjurokkasen included in the Nijuichidaishu. We thus interpret the predicted results in the classification of waka poets by LIME. The number of waka poetry data varies from poet to poet. Therefore, we adopt Naive Bayes as the classification algorithm in this work, which is expected to have high accuracy even when the number of data is small. Using LIME enables interpretation of results in the classification of waka poets; it is possible to provide rationale words for the classification results. The study of waka poetry from the point of view of data science contributes to the development of literary study by providing objective verification of hypotheses and new findings such as previously undiscovered expressions and interpretations.
瓦卡诗人分类的可解释性预测结果
在本文中,我们提出了我们的方法来提供可解释的预测结果在和歌诗人的分类。和歌是日本传统诗歌的一种。瓦卡诗反映了瓦卡诗人的思想。从和歌诗歌中提取情趣和情感,可以揭示和歌诗人的审美观念。本研究集中于《新juichidaishu》中所收录的三宿禅宗所作的和歌诗。因此,我们对石灰法对和歌诗人分类的预测结果进行了解释。和歌诗歌资料的数量因诗人而异。因此,我们在这项工作中采用朴素贝叶斯作为分类算法,即使在数据量很小的情况下,也有望具有较高的准确率。使用LIME可以解释和歌诗人分类的结果;可以为分类结果提供基本原理词。从数据科学的角度研究和歌诗歌有助于文学研究的发展,为假设和新发现(如以前未发现的表达和解释)提供客观验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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