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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22
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
2.1
ビジネスの問題をデータマイニングタスクへ
データ主導でビジネスの意思決定を行うときには、多くの場合、異なる目的・要求・制
約・利害関係者が組み合わさっているため、どのような意思決定であれそれぞれに異なった
問題であると言えます。エンジニアリング領域と同じように、データサイエンスにも問題解
決についての共通のタスクがあります。データサイエンティストはプロジェクトの利害関係
者と協力しながら、ビジネス問題に取り組むためのタスクをより小さなサブタスクへと分解
します。それらのサブタスクを解決するための方法を組み合わせることが、元の問題を解決
することにつながるのです。対象とするビジネス問題に固有のサブタスクというものもあり
ますが、多くのサブタスクはほとんどのデータマイニングに共通するタスクです。例えば、
この本で取り扱う顧客乗り換え（
churn
）問題は
MegaTelCo
社に固有の問題です。言い換
えると、
MegaTelCo
社の乗り換え問題の構造や内容は、他の携帯電話会社のそれとは異な
るのです。しかし、あらゆる乗り換え問題において、それに対応するためのパーツとなるサ
ブタスクがあります。ある顧客が契約切れのタイミングで他社に乗り換える確率を、過去の
顧客データから推定するタスクなどがそれに該当します。
MegaTelCo
社が収集したデータ
を、ある評価手法を使うことができる形式に変換することで（これについては次の章で説明
します）、乗り換え確率の推定（ ...
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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.
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.