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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6.1
LDA
■
111
## 8 area 1.371397e-03 2.310280e-04 -2.5695069
## 9 army 2.622192e-04 1.048089e-03 1.9989152
## 10 asked 1.885803e-04 1.559209e-03 3.0475641
## # ... with 188 more rows
2
つのトピックで出現頻度の差が最も大きい単語は、図6-3 に示す通りです。
図6-3 トピック2とトピック1とでβの差が大きい単語
トピ ッ ク
2
で頻 出 す る 単 語 の 中 には、「
democratic
」（民 主 ）、「
republican
」（共
和）のといった政党名、「
dukakis
」（デュカキス。
1988
年当時の民主党大統領候補）
「
gorbachev
」（ゴルバチョフ。当時のソ連最高会議幹部会議長）などの政治家の名前
が含まれています。それに対し、トピック
1
は「
yen
」や「
dollar
」といった通貨単位、
「
index
」（指数）、「
prices
」（価格）、「
rates
」（レート）といった株式に関する単語を含
んでいるところが特徴です。ここからも、アルゴリズムが探し出した
2
つのトピッ
クは、政治ニュースと株式に関するニュースだということがわかります。
6.1.2
文書
-
トピック確率
LDA
は、個々のトピックを単語の組み合わせと考えるだけでなく、文書をトピッ
クの組み合わせとしてモデリングします。
tidy()
に
matrix = "gamma" ...
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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.