WMDB: Discriminant Analysis Methods by Weight Mahalanobis Distance and bayes
Version 1.0

Distance discriminant analysis method is one of classification methods according to multiindex performance parameters.However,the traditional Mahalanobis distance discriminant method treats with the importance of all parameters equally,and exaggerates the role of parameters which changes a little.The weighted Mahalanobis distance is used in discriminant analysis method to distinguish the importance of each parameter.In the concrete application,firstly based on the principal component analysis scheme,a new group of parameters and their corresponding percent contributions of the parameters are calculated ,and the weighted matrix is regarded as the diagonal matrix of the contributions rates.Setting data to standardization,then the weighted Mahalanobis distance can be calculated.Besides the methods metioned above,bayes method is also given.

Package details

AuthorBingpei Wu
Date of publication2012-07-06 15:58:00
MaintainerBingpei Wu<[email protected]>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("WMDB")

Try the WMDB package in your browser

Any scripts or data that you put into this service are public.

WMDB documentation built on May 29, 2017, 7:22 p.m.