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- パターン認識と機械学習 下 ベイズ理論による統計的予測...
パターン認識と機械学習 下 ベイズ理論による統計的予測
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- ベイズ理論に基づく統計的予測技術は、計算アルゴリズムの開発と計算機の性能向上により、近年、急速に進展してきた。本書は、このベイズ理論に基づいた統一的な視点から、機械学習とパターン認識の様々な理論や手法を解説した教科書。この下巻では上巻の基礎的な話題を発展させた様々な手法を扱う。まず、予測精度の高さで注目を集めたサポートベクトルマシンと、今や幅広い領域で使われているカーネル法を説明。次に高度な確率モデルを表現するベイジアンネットなどのグラフィカルモデルや、潜在変数を扱うＥＭアルゴリズムを紹介。その後、ベイズ理論の適用範囲を広げた変分ベイズ法とＭＣＭＣ法について触れ、次元削減や時系列の扱いといった話題を詳説。最後に複数のモデルを結合するブースティングなどの手法を説明。
| Publisher | 丸善出版 |
| Publication date | February 29, 2012 |
| Language | Japanese |
| Print length | 433 pages |
| ISBN-10 | 4621061240 |
| ISBN-13 | 978-4621061244 |
| Item Weight | 610 g |
| Dimensions | 0.87 x 6.18 x 9.25 inches (2.2 x 15.7 x 23.5 cm) |
| Book 2 of 2 | パターン認識と機械学習 |
Product Description
パターン認識と機械学習 下 ベイズ理論による統計的予測
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