数据挖掘-实用机器学习工具与技术-(英文版.第4版)

本书特色

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本书是数据挖掘和机器学习领域的经典畅销教材，被国内外众多名校选用。第4版全面反映了该领域的新技术变革，包括关于概率方法和深度学习的重要新章节。此外，备受欢迎的机器学习软件Weka再度升级，读者可以在友好的交互界面中执行数据挖掘任务。书中的基础知识清晰详细，实践工具和技术指导具体实用，不仅适合作为高等院校相关专业的本科生或研究生教材，也可供广大技术人员参考。

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目录

PrefacePART I INTRODUCTION TO DATA MININGCHAPTER 1 What’s it all about?1.1 Data Mining and Machine LearningDescribing Structural PatternsMachine LearningData Mining1.2 Simple Examples: The Weather Problem and OthersThe Weather ProblemContact Lenses: An Idealized ProblemIrises: A Classic Numeric DatasetCPU Performance: Introducing Numeric PredictionLabor Negotiations: A More Realistic ExampleSoybean Classification: A Classic Machine Learning Success1.3 Fielded ApplicationsWeb MiningDecisions Involving JudgmentScreening ImagesLoad ForecastingDiagnosisMarketing and SalesOther Applications1.4The Data Mining Process1.5 Machine Learning and Statistics1.6 Generalization as SearchEnumerating the Concept SpaceBias1.7 Data Mining and EthicsReidentificationUsing Personal InformationWider Issues1.8 Further Reading and Bibliographic NotesCHAPTER 2 Input: concepts, instances, attributesCHAPTER 3 Output: knowledge representationCHAPTER 4 Algorithms: the basic methodsCHAPTER 5 Credibility: evaluating what’s been learnedPART II MORE ADVANCED MACHINE LEARNING SCHEMESCHAPTER 6 Trees and rulesCHAPTER 7 Extending instance-based and linear modelsCHAPTER 8 Data TransformationsCHAPTER 9 Probabilistic methodsChapter 10 Deep learningCHAPTER 11 Beyond supervised and unsupervised learningCHAPTER 12 Ensemble learningCHAPTER 13 Moving on : applications and beyondList of FiguresList of Tables

封面

书名:数据挖掘-实用机器学习工具与技术-(英文版.第4版)

作者:伊恩H.威腾

页数:621

定价:¥129.0

出版社:机械工业出版社

出版日期:2017-04-01

ISBN:9787111565277

PDF电子书大小:81MB 高清扫描完整版