Abstract
Probability theory for random vectors simple statistical decision procedures operations upon random vectors feature extraction and nonlinear mapping quadratic and linear classifiers parameter estimation nonparametric estimation and classification estimating and bounding the probability of error classification of stationary time series context-dependent methods other methods of classification.
Keywords
EstimationComputer scienceArtificial intelligencePattern recognition (psychology)Machine learningEconomicsManagement
Affiliated Institutions
Related Publications
Bootstrap Techniques for Error Estimation
The design of a pattern recognition system requires careful attention to error estimation. The error rate is the most important descriptor of a classifier's performance. The com...
Optimal Statistical Decisions.
Foreword.Preface.PART ONE. SURVEY OF PROBABILITY THEORY.Chapter 1. Introduction.Chapter 2. Experiments, Sample Spaces, and Probability.2.1 Experiments and Sample Spaces.2.2 Set ...
Classification by pairwise coupling
We discuss a strategy for polychotomous classification that involves coupling the estimating class probabilities for each pair of classes, and estimates together. The coupling m...
Estimation and Model Identification for Continuous Spatial Processes
SUMMARY Formal parameter estimation and model identification procedures for continuous domain spatial processes are introduced. The processes are assumed to be adequately descri...
Empirical Functionals and Efficient Smoothing Parameter Selection
SUMMARY A striking feature of curve estimation is that the smoothing parameter ĥ 0, which minimizes the squared error of a kernel or smoothing spline estimator, is very difficul...
Publication Info
- Year
- 1989
- Type
- article
- Volume
- 27
- Issue
- 01
- Pages
- 27-0356
- Citations
- 294
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
294
OpenAlex
Cite This
C.W. Therrien
(1989).
Decision, estimation, and classification: an introduction to pattern recognition and related topics.
Choice Reviews Online
, 27
(01)
, 27-0356.
https://doi.org/10.5860/choice.27-0356
Identifiers
- DOI
- 10.5860/choice.27-0356