Two step semi-optimal branch and bound algorithm for feature selection in mixed variable discrimination-Reference-Cited by-同舟云学术

Two step semi-optimal branch and bound algorithm for feature selection in mixed variable discrimination

Published:1989-01 Issue:4 Volume:22 Page:455-459
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Krusińska Ewa

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference12 articles.

1. Mehrdimensionale Varianzanalyse;Ahrens,1974

2. A. Bartkowiak, S. Łukasik, K. Chwistecki and M. Mrukowicz, Search for most discriminative features for CHD considering optimal and ε-optimal subsets yielded by a branch and bound method, Modelling, Simulation Control, Series C (to appear).

3. Selection of variables in mixed-variable discriminant analysis;Daudin;Biometrics,1986

4. Selection of the best subset of regression variables;Hocking,1977

5. E. Krusińska, Variable selection in location model for mixed-variable discrimination—a comparative study, Data Analysis and Informatics V. North Holland, Amsterdam (to appear).

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Variable selection in discriminant analysis for mixed continuous-binary variables and several groups;Advances in Data Analysis and Classification;2018-09-21

2. Component reduction in linear discriminant analysis;Journal of Statistical Computation and Simulation;2001-12

3. Selection in discriminant analysis with continuous and discrete variables;Computational Statistics & Data Analysis;1999-12

4. Selection of variables, and assessment of their performance, in mixed-variable discriminant analysis;Computational Statistics & Data Analysis;1995-04

5. The location model for mixtures of categorical and continuous variables;Journal of Classification;1993-01