The face_recognition_pca_lda_knn_kernelsvm_dimensionality_reduction from vivekarvind

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This project focuses on face recognition problem with respect to 5-fold cross validation, dimensionality reduction based on benchmark algorithms like K – Nearest Neighbor, Principal Component Analysis, Linear Discriminant Analysis and Kernel Support Vector Machine

MATLAB 100.00%

face_recognition_pca_lda_knn_kernelsvm_dimensionality_reduction's Introduction

1. Extract the code package.

2. Open Matlab.

3. There must be three folders in the zip file. The first folder ÔcodeÕ contains all the executable Matlab files. The other two folders are the two formats of data sets, ÔdataÕ and ÔDatasetÕ where the data is present in the respective folders and in the same folder respectively.

4. Before executing the files, paste the URI of the folder ÔDatasetÕ in the file ÔVivek_LDA.mÕ and paste the URI of the folder ÔdataÕ in all other files.

5. Execute the project by beginning with the file name ÔTask1_Vivek_PCA_KNN.mÕ and then continuing with the files in order of their Task order. There must be six files namely ÔTask1_Vivek_PCA_KNN.mÕ, ÔTask2_Vivek_KNN_resize.mÕ, ÔTask3_Vivek_LDA_KNN.mÕ,ÔTask4_Vivek_PCA_LDA_KNN.mÕ,ÔTask5_Vivek_KERNEL_SVMÕandÔTask6_Vivek_PCA_KERNEL_SVM.m'.

6. The other files are the functions which will be invoked by other functions. Those need not be executed separately.

7. The tasks involving PCA and LDA will take a long time to get executed. So other tasks can be executed first if needed.

8. Execute each file by clicking Run button on the toolbar in the Matlab window.

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