# What is the difference between quadratic and mahalanobis distance with stratified covaraiance estimates when using classify

조회 수: 2 (최근 30일)
Barry Troniqes 2014년 10월 28일
답변: Siddharth Sundar 2014년 10월 29일
Sorry for what may be a silly question but I'm very new to pattern recognition and am having trouble understanding matlabs classify function.
I have a training set for which I have performed bartlett's test for equality of covariance matrices with equal numbers of cases for each class. This returns a p of 0 which I understand to mean I should use stratified covariance estimates for each group.
classify offers two options with stratified covariance
mahalanobis — Uses Mahalanobis distances with stratified covariance estimates
Quadratic — Fits multivariate normal densities with covariance estimates stratified by group
Assuming equal priors what is the difference between performing a discriminant analysis using the mahalanobis and quadratic options? for my data the quadratic seems to perform better but I would like to understand why.

댓글을 달려면 로그인하십시오.

### 채택된 답변

Siddharth Sundar 2014년 10월 29일
The first place I would look at when trying to get some details about the Math behind the implementation would be the references mentioned in the documentation for the classify function.
Wikipedia also provides some basic information about Quadratic Discriminant Analysis(the method that is chosen when the 'type' input to the classify function is 'quadratic') as seen here.
The Mahalanobis distance and its application in discriminant analysis is also talked about in this Wikipedia page. However, I would rely on the references mentioned in the documentation page for the details.
With respect to one of the options working better than the other, from experience, that depends completely on the data that you use.

댓글을 달려면 로그인하십시오.

### 카테고리

Help CenterFile Exchange에서 Statistics and Machine Learning Toolbox에 대해 자세히 알아보기

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by