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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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.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.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.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.
138
5 章 オーバーフィッティングとその回避方法
5.8
学習曲線
トレーニングセットのサイズが変われば、結果として得られるモデルの汎化性能も変わっ
てくるはずです。データを使ったモデリングの汎化性能は、他の条件をすべて同じにした場
合、一定レベルに達するまではトレーニングデータが増えるほど良くなっていきます。ト
レーニングデータの量に対する汎化性能をプロットしたものを学習曲線（
learning curve
）
と呼びます。学習曲線も分析ツールの
1
つとして重要です。
図
5-10
乗り換え問題の交差検証におけるフォールドごとの精度。上は
20,000
個のインスタンスか
らなるデータセットを、
10
のフォールドに分割して学習させたロジスティック回帰モデル
の精度を表す。下は同じフォールドを使った分類木の精度。各グラフの水平線は、フォール
ドの平均精度を示す（精度の差を強調するために
y
軸の範囲が狭くなっていることに注意）。
ロ ジ ス ティック 回 帰
分類木
フォ ー ルド 番 号
フォ ー ルド 番 号
139
139
5.8 学習曲線
携帯電話の乗り換え問題についての、ツリー帰納法とロジスティック回帰それぞれの学習
曲線を図
5-11
に示します
†
。学習曲線の多くは、決まった形状をしています。最初が急角度
になっているのは、モデリングの過程でデータセットの中から最も特徴的な規則性を見つけ ...
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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.