项目作者： oopDaniel

项目描述：
Comparison of classification result based on dimension reduction algorithms: PCA vs LDA

高级语言： Python

项目主页：

项目地址: git://github.com/oopDaniel/COEN240-PCA-vs-LDA.git

创建时间： 2019-05-20T02:43:03Z
项目社区：https://github.com/oopDaniel/COEN240-PCA-vs-LDA
开源协议：
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Classification based on dimension reduction algorithms: PCA vs LDA

Compare Principal Component Analysis (PCA) with Linear Discriminant Analysis (LDA) / Fisher Linear Discriminant (FLD).
Use both algorithms to reduce image features into d dimension and classify different people with the reduced facial features.
The result shows that LDA works better than PCA in smaller dimensions.
Plot the accuracy rate vs reduced dimension d.

Demo

Dimension d = [1, 2, 3, 6, 9]

Dimension d = [1, 2, 3, 6, 10, 20, 30]

First time

make all

After first time

make start