July 2014
Beginner to intermediate
456 pages
11h 26m
Japanese
Content preview from 戦略的データサイエンス入門 ―ビジネスに活かすコンセプトとテクニック
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30
2 章 ビジネス問題とデータサイエンスが提供するソリューション
2.4
データマイニングプロセス
データマイニングには工芸のような側面もあります。理論に裏打ちされた科学と技術を十
分に活用できる要素を持ちながら、技巧的な要素が必要とされる余地を残しています。しか
し多くの成熟した工芸と同じように、データマイニングにも明確に定義されたプロセスがあ
り、問題解決の枠組みとして使用できます。このプロセスは合理的な一貫性と客観性を持っ
た繰り返し実行可能なプロセスです。
CRISP-DM
［
Shearer, C. 2000
］はそのようなデータ
マイニングの標準プロセスの
1
つです。図
2-2
はこのプロセスを示しています
†
。
このプロセス図から、プロセスを反復することは例外的な手順ではなく、基本的な手順で
あることがわかります。データマイニングの対象としたビジネス問題が一度のプロセスでは
解決できないこともありますが、これは失敗というわけではありません。プロセス全体にわ
たってデータの調査を行う場合が多く、一度プロセスを実施するとデータサイエンスチーム
はマイニング対象のデータに関する多くのことを学びます。そのため前回よりも多くの情報
†
Wikipedia
の
CRISP-DM
プロセスモデル（
http://wikipedia.org/wiki/Cross_Industry_Standard_
Process_for_Data_Mining
）の記事を参照してみてほしい。
図
2-1
データマイニングとデータマイニングで得られる成果の利用について。図の上半分は過去の ...
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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.
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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.