Xiaoyang-Rebecca / PatternRecognition_Matlab

Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).

Date Created 2017-10-18 (7 years ago)

Commits 12 (last one 3 years ago)

Stargazers 72 (0 this week)

Watchers 2 (0 this week)

Forks 22

License unknown

Ranking

RepositoryStats indexes 628,836 repositories, of these Xiaoyang-Rebecca/PatternRecognition_Matlab is ranked #382,522 (39th percentile) for total stargazers, and #479,762 for total watchers. Github reports the primary language for this repository as MATLAB, for repositories using this language it is ranked #732/1,620.

Other Information

Xiaoyang-Rebecca/PatternRecognition_Matlab has Github issues enabled, there is 1 open issue and 4 closed issues.

Homepage URL: https://www.researchgate.net/publication/308927930_Comparison_of_Feature_Reduction_Approaches_and_Classification_Approaches_for_Pattern_Recognition

All Topics

gmm lda pca svm kpca pattern-recognition gaussian-mixture-models

Star History

Github stargazers over time

Watcher History

Github watchers over time, collection started in '23

Recent Commit History

0 commits on the default branch (master) since jan '22

No recent commits to this repository

Yearly Commits

Commits to the default branch (master) per year

Issue History

Languages

The primary language is MATLAB but there's also others...

updated: 2025-01-15 @ 09:17am, id: 107423607 / R_kgDOBmcndw