Predicting Structured Data (Hardcover)
暫譯: 預測結構化數據 (精裝版)
Gökhan H. Bakir, Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola
- 出版商: MIT
- 出版日期: 2007-07-27
- 售價: $1,500
- 貴賓價: 9.5 折 $1,425
- 語言: 英文
- 頁數: 360
- 裝訂: Hardcover
- ISBN: 0262026171
- ISBN-13: 9780262026178
-
相關分類:
Machine Learning
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商品描述
Description
Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning’s greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.
商品描述(中文翻譯)
**描述**
機器學習發展出能夠從先前見過的範例中進行概括的智能計算機系統。機器學習的一個新領域要求預測必須滿足結構化數據中的額外約束，這對機器學習來說是一個最大的挑戰之一：學習任意輸入和輸出領域之間的功能依賴性。本書介紹並分析了這一新領域中機器學習算法和理論的最新進展。貢獻者討論了多種應用，包括機器翻譯、文檔標記、計算生物學和信息提取等，提供了對這一令人興奮的領域的及時概述。
