Data analysis / edited by Gerard Govaert.

Format:

Book

Contributor:

Govaert, Gérard.

Series:

ISTE

ISTE ; v.136

Standardized Title:

Analyse des donnees. English.

Language:

English

Subjects (All):

Mathematical statistics.

Data mining.

Physical Description:

1 online resource (343 p.)

Edition:

1st ed.

Place of Publication:

Hoboken, NJ : Wiley, c2009.

Language Note:

English

Summary:

The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data. The book concludes by examining the links existing between data mining and data analysis.

Contents:

Data Analysis; Contents; Preface; Chapter 1. Principal Component Analysis: Application to Statistical Process Control; 1.1. Introduction; 1.2. Data table and related subspaces; 1.2.1. Data and their characteristics; 1.2.2. The space of statistical units; 1.2.3. Variables space; 1.3. Principal component analysis; 1.3.1. The method; 1.3.2. Principal factors and principal components; 1.3.3. Principal factors and principal components properties; 1.4. Interpretation of PCA results; 1.4.1. Quality of representations onto principal planes; 1.4.2. Axis selection; 1.4.3. Internal interpretation

1.4.4. External interpretation: supplementary variables and individuals1.5. Application to statistical process control; 1.5.1. Introduction; 1.5.2. Control charts and PCA; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Correspondence Analysis: Extensions and Applications to the Statistical Analysis of Sensory Data; 2.1. Correspondence analysis; 2.1.1. Data, example, notations; 2.1.2. Questions: independence model; 2.1.3. Intensity, significance and nature of a relationship between two qualitative variables; 2.1.4. Transformation of the data; 2.1.5. Two clouds; 2.1.6. Factorial analysis of X

2.1.7. Aid to interpretation2.1.8. Some properties; 2.1.9. Relationships to the traditional presentation; 2.1.10. Example: recognition of three fundamental tastes; 2.2. Multiple correspondence analysis; 2.2.1. Data, notations and example; 2.2.2. Aims; 2.2.3. MCA and CA; 2.2.4. Spaces, clouds and metrics; 2.2.5. Properties of the clouds in CA of the CDT; 2.2.6. Transition formulae; 2.2.7. Aid for interpretation; 2.2.8. Example: relationship between two taste thresholds; 2.3. An example of application at the crossroads of CA and MCA; 2.3.1. Data

2.3.2. Questions: construction of the analyzed table2.3.3. Properties of the CA of the analyzed table; 2.3.4. Results; 2.4. Conclusion: two other extensions; 2.4.1. Internal correspondence analysis; 2.4.2. Multiple factor analysis (MFA); 2.5. Bibliography; Chapter 3. Exploratory Projection Pursuit; 3.1. Introduction; 3.2. General principles; 3.2.1. Background; 3.2.2. What is an interesting projection?; 3.2.3. Looking for an interesting projection; 3.2.4. Inference; 3.2.5. Outliers; 3.3. Some indexes of interest: presentation and use; 3.3.1. Projection indexes based on entropy measures

3.3.2. Projection indexes based on L2 distances3.3.3. Chi-squared type indexes; 3.3.4. Indexes based on the cumulative empirical function; 3.4. Generalized principal component analysis; 3.4.1. Theoretical background; 3.4.2. Practice; 3.4.3. Some precisions; 3.5. Example; 3.6. Further topics; 3.6.1. Other indexes, other structures; 3.6.2. Unsupervised classification; 3.6.3. Discrete data; 3.6.4. Related topics; 3.6.5. Computation; 3.7. Bibliography; Chapter 4. The Analysis of Proximity Data; 4.1. Introduction; 4.2. Representation of proximity data in a metric space

4.2.1. Four illustrative examples

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on metadata supplied by the publisher and other sources.

ISBN:

1-282-68434-5

9786612684340

0-470-61177-4

0-470-61031-X

OCLC:

609853549