Departmental Bulletin Paper Heat Map with Hierarchical Clustering: Multivariate Visualization Method for Corpus-based Language Studies
ヒートマップと階層型クラスタリング : コーパスに基づく言語研究のための多変量視覚化手法

小林, 雄一郎  ,  Yuichiro, KOBAYASHI

(11)  , pp.25 - 36 , 2016-07 , 国立国語研究所
ISSN:2186-134x print2186-1358 online
An advantage of corpus-based language studies is that global descriptions of linguistic texts can be obtained by examining a broad range of linguistic features. However, multivariate statistical techniques are required to analyze the multiple linguistic features found in a number of texts. This study compared the strengths and weaknesses of several multivariate statistical techniques, thereby demonstrating the effectiveness of using heat map with hierarchical clustering as a powerful method for visualizing multivariate data. Explanations are also provided for how these techniques can be used in the R programming language as well as indicating how the results obtained can be interpreted.

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