Principal Component Analysis (PCA)

PCA : reduce features used in face recognition

- This program uses Principal Component Analysis to reduce the number of features used in face recognition.
- This program allows you to set K if you know the number of Principal components needed or calculates K based on how much variance you would like to preserve in the images.
- The images consisting of reduced features can be used for training a neural network or logistic regression model.
- It decreases computation time of the program.
- Original & recovered images displayed