发表于2024-11-07
Data Mining 2024 pdf epub mobi 电子书
翻译的不大好,譬如:指针与引用的"引用(reference)",被翻译成"参考";JavaBean被翻译为Java豆;异常的"抛出"被翻译为"丢弃".... 不过对于想学习Weka,研究Weka源码的朋友来说,该书的算法介绍和软件使用还是很不错的.
评分国内教科书都是先进来源、历史、分类、发展、趋势等。外国人写的上来稍微介绍一下就像专业知识进军啦
评分作者可以说是享誉盛名,但是这本书写出来,基本上章法全无。理论和例子基本上没有几个是适合入门者的,加上翻译有些地方表意不清。初阶入门者看了的话,肯定一团迷雾。 评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评论太短了嘛?评...
评分这本dm的书啃完了,觉得有点这个书有点“偏见”,怎么理解呢 前面的东西不错哦,可是后半部分的Weka平台我个人觉得翻翻就行了,要学还不如看看spss的书呢,前面关于机器模型的建立的数学基础要求的不是很高,所以很适合一般没有学过随机过程的人看看,要是数学很牛的人,可以看...
评分我觉得,可以当作weka的使用手册来看,但是比weka自带的指南写的好看。 算法部分的介绍很详细。
图书标签: 数据挖掘 机器学习 DataMining MachineLearning weka 计算机 计算机科学 CS
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.
*Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects *Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods *Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
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评分WEKA说明书第三版,相比第二版有增加内容,不过还是基于WEKA的,简单用用还行。
评分textbook
评分weka
评分讲解的内容不错 全书结构略显混乱 阅读时自带超链接跳转/书签会比较好follow...
Data Mining 2024 pdf epub mobi 电子书