October 2017
Intermediate to advanced
480 pages
9h 49m
Japanese
Content preview from Rではじめるデータサイエンス
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19.4
モデルについてさらに学ぶには
351
3. 変数
wday
を土曜日だけ学期ごとに分ける。すなわち、
Thurs
,
Fri
,
Sat-summer
,
Sat-spring
,
Sat-fall
となる新たな変数を作りなさい。このモデルは、
wday
と
term
のあらゆる組み合わせを
したモデルと比較してどうか。
4. 曜日、（土曜日の）学期、祝日を組み合わせた新たな
wday
変数を作りなさい。このモデルの残差
はどのようになるか。
5. 月によって変動する曜日効果にモデル適合させる（すなわち、
n ~ wday * month
）と何が起こる
か。なぜこれはそれほど役立たないのか。
6. モデル
n ~ wday + ns(date, 5)
はどのようだと期待するか。データからわかることから、なぜ
これがそれほど効果的でないかを説明しなさい。
7. 日曜に出発する人は、月曜にどこかに行かなければならないビジネスマンだという仮説
を立て
た。この仮説を、距離と時刻に基づいてどのように細分化できるか、もし仮説が真なら、遠く
の場所には日曜夜の便がより多くなる、などを探索しなさい。
8. 土曜と日曜がプロットの両端に分かれているのは少々面倒だ。月曜から週が始まるようにファク
タの水準を設定する関数を書きなさい。
19.4
モデルについてさらに学ぶには
本章ではモデル化という世界の表面をなぞっただけですが、データ分析能力の改善に使える単純
だが汎用のツールが得られたものと期待します。単純なところから始めるのはよいことです ...
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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.