May 2018
Intermediate to advanced
228 pages
4h 11m
Japanese
Content preview from Rによるテキストマイニング ―tidytextを活用したデータ分析と可視化の基礎
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90
■
5
章 未整理形式へ（から）の変換
図5-4
4つの選択した単語の大統領就任演説における出現頻度が時代とともに変化する様子
これらの例は、
tidytext
と関連する整理ツールスイートを使えば、もとのデータ
が整理形式になっていない場合でも分析できることがわかります。
5.2
整理データの行列へのキャスト
既存のテキストマイニングパッケージがサンプルデータや出力として
DTM
を使
用しているのと同じように、その種の行列を入力とするアルゴリズムもあります。
そこで、
tidytext
は、整理形式から
DTM
への変換を行う
cast_
機能を提供していま
す。
たとえば、
cast_dtm()
関数を使えば、整理された
AP
通信記事のデータセットを
DTM
形式に戻すことができます。
ap_td %>%
cast_dtm(document, term, count)
## <<DocumentTermMatrix (documents: 2246, terms: 10
473)>>
## Non-/sparse entries: 302031/23220327
## Sparsity : 99%
## Maximal term length: 18
5.2
整理データの行列へのキャスト
■
91
## Weighting : ...
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