Discriminant analysis and clustering / National Research Council.

Format:

Book

Author/Creator:

National Research Council (U.S.), author.

Contributor:

National Research Council (U.S.). Committee on Applied and Theoretical Statistics.

National Research Council (U.S.). Panel on Discriminant Analysis, Classification, and Clustering.

Language:

English

Subjects (All):

Discriminant analysis.

Cluster analysis.

Mathematical statistics.

Physical Description:

1 online resource (116 p.)

Edition:

1st ed.

Place of Publication:

Washington, District of Columbia : National Academy Press, 1988.

Language Note:

English

Contents:

Discriminant Analysis and Clustering; Copyright; PREFACE; Contents; CHAPTER 1 INTRODUCTION; CHAPTER 2 METHODS; 2.1 INTRODUCTION; 2.2 METHODS OF DISCRIMINANT ANALYSIS; 2.2.1 General Remarks; 2.2.2 Classical Two-group Linear Discriminant Analysis; Relation to Regression Analysis; Tests of Hypotheses; Advantages of the LDF; Variable Selection; 2.2.3 Classification Into One of Several Populations; 2.2.4 Heterogeneous Covariance Matrices Case; The Quadratic Discriminant Function; Best Linear Discriminant Function; 2.2.5 Two-group Classification by Logistic Regression; Strengths and Weaknesses

2.2.6 Kernel and Nearest Neighbor Methods2.2.7 Classification Trees; 2.3 METHODS OF CLUSTER ANALYSIS; 2.3.1 General Remarks; 2.3.2 Algorithms; 2.3.3 Perspective; CHAPTER 3 THEORY; 3.1 INTRODUCTION; 3.2 THEORETICAL ISSUES IN DISCRIMINANT ANALYSIS; 3.2.1 Introduction; 3.2.2 The Fisher Linear Discriminant and Some of Its Children; 3.2.3 Estimating Misclassification Costs; 3.2.4 Nonparametric Techniques; 3.3 STATISTICAL THEORY IN CLUSTERING; 3.3.1 Introduction; 3.3.2 High Density Clusters; 3.3.3 Agglomerative Methods for High Density Clusters

3.3.4 Single Linkage, the Minimum Spanning Tree and Percolation3.3.5 Mixtures; 3.3.6 The Number of Clusters: Modes; 3.3.7 The Number of Clusters: Components; 3.3.8 Ultrametric and Evolutionary Distances; CHAPTER 4 SOFTWARE AND ALGORITHM IMPLEMENTATION; 4.1 INTRODUCTION; 4.2 DISCRIMINANT ANALYSIS; 4.2.1 Linear and Quadratic Discriminant Functions; 4.2.2 Review of Packages; P-STAT; SPSS-X; BMDP7M; SAS PROCEDURES; Other Packages; 4.2.3 Logistic Regression; 4.2.4 Classification Trees; 4.3 CLUSTER ANALYSIS; 4.3.1 Collections of Subroutines and Algorithms

Statistical Packages Containing Clustering Software4.3.2 Cluster Analysis Packages; 4.3.3 Simple Cluster Analysis Programs; 4.4 NEEDS; CHAPTER 5 CLOSING PERSPECTIVE; REFERENCES

Notes:

Description based upon print version of record.

Includes bibliographical references.

Description based on online resource; title from PDF title page (ebrary, viewed February 12, 2016).

OCLC:

744953227