Analysis of symbolic data符号数据分析：从复杂数据中析取统计信息的探索性方法（丛书） umd mobi chm 夸克云 免费 azw3 下载 pdf

This first systematic and self-contained monograph on "Symbolic Data Analysis" presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data where the entries of a data table are, e. g., sets of categories or of numbers, intervals or probability distributions. Typical methods include: graphical displays using Zoom Stars, visualization and feature extraction by symbolic factor analysis, decision trees, discrimination, classification and clustering methods. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.

Preface of the Scientific Editors

Preface of the Project Managers

1 Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective

　1.1 Introduction

　1.2 Symbolic Data Tables and Symbolic Objects

　　1.2.1 The Input of SDA: Symbolic Data Tables, Rules and Taxonomies

　　1.2.2 Sources of Symbolic Data

　　1.2.3 Symbolic Objects

　1.3 Tools and Operations for Symbolic Objects

　1.4 History and Evolution of SDA

　1.5 The Content of the SODAS Project

　　1.5.1 SDA Methods Realized in SODAS

　　1.5.2 An Illustrative Example

　　1.5.3 Overview on the SODAS Software

　　1.5.4 Examples for the SODAS Strategy in Applications

　1.6 Philosophical Background: Concepts and Symbolic Objects

　　1.6.1 First- and Second-Order Individuals

　　1.6.2 Intent and Extent, the Two Kinds of Concepts

　　1.6.3 Concepts: The Four Traditions and 'Symbolic Objects'

　1.7 Advantages of Using Symbolic Data Analysis

　1.8 The Future Development of SODAS

2 The Classical Data Situation

　2.1 Introduction

　2.2 Variables as Input Data

　2.3 Quantitative Variables

　2.4 Qualitative Variables

　　2.4.1 Nominal Variables

　　2.4.2 Ordinal Variables and Generalized Ordinal Variables

　2.5 Data Vectors and the Data Matrix

　2.6 Dependent Variables

　　2.6.1 Logical Dependence

　　2.6.2 Hierarchical Dependence (Mother-Daughter)

　　2.6.3 Stochastic Dependence

　2.7 Missing Values

3 Symbolic Data

　3.1 Three Introductory Examples

　3.2 Multi-Valued and Interval Variables

　3.3 Modal Variables

　3,4 A Synthesis of Symbolic Data Types

　3.5 The Symbolic Data Array

4 Symbolic Objects

　4.1 Introduction and Examples

　4.2 Relations and Descriptions

　　4.2.1 Relations

　　4.2.2 Descriptions, Description Vectors and Description Sets

　　4.2.3 Product Relations

　4,3 Events and Assertion Objects

　4.4 Boolean Symbolic Objects as Triples

　4.5 Modal Symbolic Objects

5 Generation of Symbolic Objects from Relational Databases

　5.1 Introduction to Relational Databases

　5.2 Principles of Symbolic Object Acquisition from Relational Databases

　5.3 Interaction with the Database

5.3.1 Interpretation of SQL Queries

……

6 Descriptive Statistics for Symbolic Data

7 Visualizing and Editing Symbolic Objects

8 Similarity and Dissimilarity

9 Symbolic Factor Analysis

10 Discrimination: Assigning Symbolic Objects to Classes

11 Clustering Methods for Symbolic Objects

12 Symbolic Approaches for Three-way Data

13 Illustrative Benchmark Analyses

14 The SODAS Software Package

Notations and Abbreviations

Bibliography

Addresses of Contributors to this Volume

Subject Index

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