C4.5: Programs for Machine Learning (Paperback)
J. Ross Quinlan
- 出版商: Morgan Kaufmann
- 出版日期: 1992-10-01
- 定價: $2,500
- 售價: 8.0 折 $2,000 (限時優惠至 2024-12-31)
- 語言: 英文
- 頁數: 302
- 裝訂: Paperback
- ISBN: 1558602380
- ISBN-13: 9781558602380
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相關分類:
Machine Learning
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商品描述
Order This Book | Authors | Contents | Related Titles
Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. The source code and sample datasets are also available for download (see below).
C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies.
This book and software should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.
J. Ross Quinlan, University of New South Wales
- 1 Introduction
2 Constructing Decision Trees
3 Unknown Attribute Values
4 Pruning Decision Trees
5 From Trees to Rules
6 Windowing
7 Grouping Attribute Values
8 Interacting with Classification Models
9 Guide to Using the System
10 Limitations
11 Desirable Additions
Appendix: Program Listings
Resources
- Release 8 does not correspond exactly to the version referred to in the book, Release 5
- this software is compatible with Sun IPC or ELC workstation
- please note following restrictions:
This software is distributed "as is," without warranty of any kind, either expressed or implied, including but not limited to implied warranties of merchantability or fitness for a particular purpose. It is Copyright 1987, 1988, 1989, 1990, 1991, 1992 by J.R. Quinlan. All rights reserved. This software may not be distributed in any form without permission of the copyright holder.
商品描述(中文翻譯)
訂購這本書 | 作者 | 目錄 | 相關書籍
分類器系統在機器學習和基於知識的系統中扮演著重要角色,Ross Quinlan在ID3和C4.5上的工作被廣泛認為對其發展做出了最重要的貢獻。本書是C4.5系統的完整指南,該系統在UNIX環境中使用C語言實現。它包含了對系統使用的全面指南,源代碼(約8800行)和實現筆記。源代碼和樣本數據集也可供下載(見下文)。
C4.5從屬於已知類別的大量案例開始。這些案例由任何混合的名義和數值屬性描述,並且被仔細檢查以找出可以可靠區分類別的模式。然後,這些模式以決策樹或if-then規則集的形式表達,可以用於對新案例進行分類,並強調使模型易於理解和準確。該系統已成功應用於涉及數以萬計的案例和數百個屬性的任務。本書從簡單的核心學習方法開始,並展示了如何擴展和擴展這些方法以應對典型問題,如缺失數據和過度擬合。 C4.5方法的優點和缺點將通過幾個案例研究進行討論和說明。
本書和軟件將對基於分類的智能系統的開發人員以及機器學習和專家系統課程的學生感興趣。
作者:
J. Ross Quinlan,新南威爾士大學
目錄:
1 介紹
2 構建決策樹
3 未知屬性值
4 剪枝決策樹
5 從樹到規則
6 窗口化
7 屬性值分組
8 與分類模型互動
9 使用該系統的指南
10 限制
11 理想的增加
附錄:程序清單
資源:
C4.5 Release 8
- Release 8與書中提到的版本不完全相符
- 此軟件與Sun IPC或ELC工作站兼容
- 請注意以下限制:
- 此軟件按原樣分發,不提供任何明示或暗示的保證,包括但不限於適銷性或特定用途的暗示保證。版權所有 1987, 1988, 1989, 1990, 1991, 1992 J.R. Quinlan。保留所有權利。未經版權持有人許可,不得以任何形式分發此軟件。
相關書籍:
- 人工智能
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