May 2020
Intermediate to advanced
456 pages
9h 13m
Japanese
Content preview from ゼロからはじめるデータサイエンス 第2版 ―Pythonで学ぶ基本と実践
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174
■
11
章 機械学習
N
データポイントによる
9
次多項式のあてはめ
図 11-2 データの追加による、バリアンスの低減
11.6
特徴抽出と特徴選択
前述したように、データに十分な特徴が含まれていなければ、そこから作られるモ
デルは未学習となる傾向があります。多くの特徴が盛り込まれているなら、過学習に
なりがちです。ところで、ここで言う特徴とは何者であり、どこからもたらされるもの
なのでしょう。
特徴とは、モデルに対するあらゆる入力が相当します。
最も単純なケースでは、与えられたデータだけが特徴です。誰かの収入を勤続年数
を元に判断する場合、この勤続年数が唯一の特徴です（しかし、「11.3 過学習と未学
習」で見たように、より良いモデルを作るのに役立つのであれば勤続年数の
2
乗や
3
乗
などを加えることも考慮するかもしれません）。
データが複雑性を増せば、より興味深い状況となります。メールメッセージがスパ
ムであるかどうかを判断するフィルタを作るとしましょう。普通のモデルなら、単なる
テキストであるメールをそのままで判断には使えません。そこで特徴を抽出する必要
があります。
●
メッセージに「ビットコイン」という単語が含まれているか
●
文字
d
が何回使われているか
●
メールがどのドメインから発信されているか
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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.