Data Mining pdf epub mobi txt 电子书下载 2026

简体网页||繁体网页

☆☆☆☆☆

出版者:Morgan Kaufmann

作者:Ian H. Witten

出品人:

页数:664

译者:

出版时间:2011-1-20

价格:GBP 42.99

装帧:Paperback

isbn号码:9780123748560

丛书系列:

图书标签:

数据挖掘
机器学习
DataMining
MachineLearning
weka
计算机
计算机科学
CS
数据挖掘
机器学习
数据分析
人工智能
统计学习
模式识别
大数据
算法
数据库
知识发现

下载链接在页面底部

facebook linkedin mastodon messenger pinterest reddit telegram twitter viber vkontakte whatsapp 复制链接

想要找书就要到小美书屋

book.quotespace.org

立刻按 ctrl+D收藏本页

你会得到大惊喜!!

具体描述

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

作者简介

目录信息

读后感

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☆☆☆☆☆

一会是查询偏差，一会是搜索偏差~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

评分☆☆☆☆☆

----------------------------------------- 外文教材，外文参考书请咨询 http://shop35575714.taobao.com ----------------------------------------

评分☆☆☆☆☆

这本书虽然标题是Data Mining，但是核心内容还是机器学习。我理解“数据挖掘”主要指的还是KDD，即基于数据库的知识发现。在这个领域，基本的方法是聚类和关联规则发现；而在机器学习领域，主要研究的是分类。这本书的内容主要是分类，也有一部分聚类的内容，关联规则发现基...