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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5.1
DTM
の整理
■
83
とんどのテキストマイニングパッケージの入力として整理データフレームを使えな
いのと同じです。そこで、
tidytext
パッケージは、
2
つの形式の間の相互変換のため
に
2
つの関数を提供しています。
●
tidy()
関数は、
DTM
を整理データフレームに変換します。これは、さまざ
まな統計モデルやオブジェクトのために整理関数を提供している
broom
パッ
ケージ（
Robinson 2017
）に由来するものです。
●
cast()
は、
1
行
1
単語の整理データフレームを行列に変換します。
tidytext
の
この関数には
3
種類のものがあり、それぞれ異なるタイプの行列への変換を行
います。
cast_sparse()
は
Matrix
パッケージの疎行列、
cast_dtm()
は
tm
パッ
ケージの
DocumentTermMatrix
オブジェクト、
cast_dfm()
は
quanteda
の
dfm
オ
ブジェクトを出
力します。
図5-1 に示すように、
DTM
は
count
や
group_by
/
summarize
を実行したあとの整理
データフレームと同じように、単語と文書の組み合わせの出現頻度、その他の統計
情報を格納しています。
5.1.1
DocumentTermMatrix
オブジェクトの整理
R
で最も広く使われている
DTM
は、おそらく
tm
パッケージの
DocumentTermMatrix
クラスでしょう。多くのテキストマイニングデータセットがこの形式で提供され
ています。たとえば、
topicmodels
パッケージ
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.