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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79
79
3.4 ルールの集まりとしてのツリー
す。分類木の次のノードは、属性「年齢」を基準値
45
で評価します。これは、この図にお
いては年齢
=45
のところに引かれた横線に対応します。この線はこの図の右側にしか出てき
ません。なぜなら、この分割は残高≧
50
のインスタンスに対してだけしか適用しないから
です。年齢を評価するノードの左のブランチの先には、年齢＜
45
のインスタンスが割り当
たっており、それらは図中の右下の部分に対応します（残高≧
50K
かつ年齢＜
45
）。
内部ノード（決定ノード、
decision node
）はそれぞれ、インスタンス空間を分割する線に
相当することに注意してください。リーフノードはインスタンス空間における分割後のそれ
ぞれの領域（母集団を分割したセグメント）に相当します。木の経路をたどって内部ノード
を進むにつれて、たどり着く場所はインスタンス空間を分割する線で定義された
1
つか
2
つ
の領域に限定されていきます。分類木を下っていくと、インスタンス空間内のある領域に絞
り込まれていくのです。
決定線と超平面
2 次元のインスタンス空間内の領域を分割している線は決定線（decision lines）
と呼ばれます。3 次元以上の場合には決定面（decision surfaces）あるいは決
定境界（decision boundaries）と呼ばれます。分類木のノードでは、1 つの属
性をある値と比較して評価します。決定線あるいは決定面は、属性を表す軸に対し
て常に垂直になります。2 次元の場合には、その線は縦線か横線となります。もし ...
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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.