August 2015
Intermediate to advanced
312 pages
7h 28m
Japanese
Content preview from 初めてのSpark
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244
11 章 MLlib を使った機械学習
11.5
テクニックフーンの
11.5.1
特徴の
機械学習のプレゼンテーションでは、使用されるアルゴリズムが強調されることがよくあります
が、実際にはどのアルゴリズムであっても、用意された特徴以上に良くなることはないと覚えてお
かなければなりません！
大規模な機械学習を実践している人々の多くは、特徴の準備こそが、大
規模な学習における最も重要なステップであることに同意してくれることでしょう。情報量の多い
特徴を追加すること（例えば他のデータセットと結合して情報を増やす）や、利用可能な特徴を変
換して、適切なベクトル表現にすること（例えばベクトルの標準化）によって、結果が大きく改善
されることがあります。
特徴の用意に関する十全な議論は本書の範囲を超えるものなので、詳しい情報については機械学
習に関する他のテキストを参照することをお勧めします。ただし、特に
MLlib
については、一般
的に次のようなテクニックが使われます。
•
入力する特徴を標準化してください。「
11.4.3
標準化」で説明したように、
StandardScaler
に特徴を通すことで、特徴の重みを均等にしてください。
•
テキストからの特徴抽出を適切に行ってください。
NLTK
（
http://www.nltk.org
）のよ
うな外部のライブラリを使って単語のステミングを行い、
TF-IDF
のために代表的なコー
パスに渡って
IDF
を使用してください。
•
クラスを適切にラベル付けしてください。 ...
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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.