April 2025
Intermediate
240 pages
6h 56m
Japanese
Content preview from AI開発力を鍛える！機械学習と最適化による問題解決講座
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048
0
1
2
3
2
2.1
機械学習手法は何を使えば
よいか？：目的の観点から
機械学習手法の選択は、機械学習応用の成否を決める非常に重要な過程で
す。しかし重要であるからこそ、手法の中身や工夫ばかりに目が行ってしま
い、本来の目的や解決したかった課題からはピントが外れた解析や予測を
行ってしまうこともしばしば見かけます。まず本節では、機械学習を行う目
的の観点から、パラメトリックモデルとノンパラメトリックモデルの違い、
そして統計解析と機械学習の違いを学びながら機械学習手法の選択方法につ
いて考えます。
パ ラ メトリッ ク モ デ ル とノ ン パ ラ メトリッ ク モ デ ル の
どちらを使えばよいか？
機械学習手法の選択を考える際、大本となる分類は何でしょうか。分類木を用
いて機械学習手法の種類を分析した場合に、一番根元の分岐は何になるでしょう
か。様々な分類の仕方がありますが、応用の観点からは、パラメトリックモデル
を用いるか、ノンパラメトリックモデルを用いるかが一番初めの分岐になるで
しょう（
図 2.1.1）。パラメトリックとノンパラメトリックの違いには様々な説明
がありますが、最もわかりやすく言うと、特定の数式を定めてその係数を求める
場合（パラメトリック）と特定の数式を定めない場合（ノンパラメトリック）と
説明できます。
2.1.1
2.
3.
0.
1.
049
2.1
図 2.1.1 応用の観点から機械学習の分類を表す分類木
パラメトリック回帰には、理学や工学で、いわゆる「理論式でフィッティング ...
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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.