數據挖掘導論（英文版） pdf epub mobi txt 电子书 下载 2025

☆☆☆☆☆

[美] 譚，斯坦巴剋，庫馬爾 著

出版社： 机械工业出版社

ISBN：9787111316701

版次：1

商品编码：10350780

品牌：机工出版

包装：平装

丛书名： 经典原版书库

开本：16开

出版时间：2010-09-01

用纸：胶版纸

页数：769

內容簡介

《數據挖掘導論（英文版）》全麵介紹瞭數據挖掘的理論和方法，著重介紹如何用數據挖掘知識解決各種實際問題，涉及學科領域眾多，適用麵廣。書中涵蓋5個主題：數據、分類、關聯分析、聚類和異常檢測。除異常檢測外，每個主題都包含兩章：前麵一章講述基本概念、代錶性算法和評估技術，後麵一章較深入地討論高級概念和算法。目的是使讀者在透徹地理解數據挖掘基礎的同時，還能瞭解更多重要的高級主題。包含大量的圖錶、綜閤示例和豐富的習題。·不需要數據庫背景。隻需要很少的統計學或數學背景知識。·網上配套教輔資源豐富，包括PPT、習題解答、數據集等。

目錄

Preface
1 Introduction
1.1 What Is Data Mining?
1.2 Motivating Challenges
1.3 The Origins of Data Mining
1.4 Data Mining Tasks
1.5 Scope and Organization of the Book
1.6 Bibliographic Notes
1.7 Exercises
2 Data
2.1 Types of Data
2.1.1 Attributes and Measurement
2.1.2 Types of Data Sets
2.2 Data Quality
2.2.1 Measurement and Data Collection Issues
2.2.2 Issues Related to Applications
2.3 Data Preprocessing
2.3.1 Aggregation
2.3.2 Sampling
2.3.3 Dimensionality Reduction
2.3.4 Feature Subset Selection
2.3.5 Feature Creation
2.3.6 Discretization and Binarization
2.3.7 Variable Transformation
2.4 Measures of Similarity and Dissimilarity
2.4.1 Basics
2.4.2 Similarity and Dissimilarity between Simple Attributes.
2.4.3 Dissimilarities between Data Objects
2.4.4 Similarities between Data Objects
2.4.5 Examples of Proximity Measures
2.4.6 Issues in Proximity Calculation
2.4.7 Selecting the Right Proximity Measure
2.5 Bibliographic Notes
2.6 Exercises
3 Exploring Data
3.1 The Iris Data Set
3.2 Summary Statistics
3.2.1 Frequencies and the Mode
3.2.2 Percentiles
3.2.3 Measures of Location: Mean and Median
3.2.4 Measures of Spread: Range and Variance
3.2.5 Multivariate Summary Statistics
3.2.6 Other Ways to Summarize the Data
3.3 Visualization
3.3.1 Motivations for Visualization
3.3.2 General Concepts
3.3.3 Techniques
3.3.4 Visualizing Higher-Dimensional Data
3.3.5 Do's and Don'ts
3.4 OLAP and Multidimensional Data Analysis
3.4.1 Representing Iris Data as a Multidimensional Array
3.4.2 Multidimensional Data: The General Case
3.4.3 Analyzing Multidimensional Data
3.4.4 Final Comments on Multidimensional Data Analysis
3.5 Bibliographic Notes
3.6 Exercises
Classification:
4 Basic Concepts, Decision Trees, and Model Evaluation
4.1 Preliminaries
4.2 General Approach to Solving a Classification Problem
4.3 Decision Tree Induction
4.3.1 How a Decision Tree Works
4.3.2 How to Build a Decision Tree
4.3.3 Methods for Expressing Attribute Test Conditions .
4.3.4 Measures for Selecting the Best Split
4.3.5 Algorithm for Decision Tree Induction
4.3.6 An Example: Web Robot Detection
4.3.7 Characteristics of Decision Tree Induction
4.4 Model Overfitting
4.4.1 Overfitting Due to Presence of Noise
4.4.2 Overfitting Due to Lack of Representative Samples .
4.4.3 Overfitting and the Multiple Comparison Procedure
4.4.4 Estimation of Generalization Errors
4.4.5 Handling Overfitting in Decision Tree Induction . .
4.5 Evaluating the Performance of a Classifier
4.5.1 Holdout Method
4.5.2 Random Subsampling
4.5.3 Cross-Validation
4.5.4 Bootstrap
4.6 Methods for Comparing Classifiers
4.6.1 Estimating a Confidence Interval for Accuracy
4.6.2 Comparing the Performance of Two Models
4.6.3 Comparing the Performance of Two Classifiers
4.7 Bibliographic Notes
4.8 Exercises
5 Classification: Alternative Techniques
6 Association Analysis: Basic Concepts and Algorithms

精彩書摘

Pang.Ning Tan現為密歇根州立大學計算機與工程係助理教授，主要教授數據挖掘、數據庫係統等課程。他的研究主要關注於為廣泛的應用（包括醫學信息學、地球科學、社會網絡、Web挖掘和計算機安全）開發適用的數據挖掘算法。
Michael Steinbach擁有明尼蘇達大學數學學士學位、統計學碩士學位和計算機科學博士學位，現為明尼蘇達大學雙城分校計算機科學與工程係助理研究員。
Vipin Kumar現為明尼蘇達大學計算機科學與工程係主任和William Norris教授。1 988年至2005年。他曾擔任美國陸軍高性能計算研究中心主任。
……

前言/序言

alt="" />

评分☆☆☆☆☆

大数据真火爆……好像不会编程就不是人一样。

评分☆☆☆☆☆

买来学习专业术语

评分☆☆☆☆☆

很经典的书。

评分☆☆☆☆☆

不解释，经典之作！

评分☆☆☆☆☆

提前囤书，数据挖掘经典教程

评分☆☆☆☆☆

品质很好，非常喜欢。

评分☆☆☆☆☆

物流很快，书质量还行

评分☆☆☆☆☆

商品满意度5分 请至少填写一件商品的评价

评分☆☆☆☆☆