Data_Science_Image_Classification_With_PCA_and_..._Classifier

Transforming a dataset of images, into their eigen-faces/eigen-vectors with PCA, then selecting the main of those vectors and applying unsupervised classification. The classifier used for the transformed data set, after applying PCA, is ... The number of eigen-faces selected, have a 95% correct representation of the original image. The source dataset of images is added as a folder in the project, although it can also be extracted from the following link: https://estudusfqedu-my.sharepoint.com/personal/nperez_usfq_edu_ec/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fnperez%5Fusfq%5Fedu%5Fec%2FDocuments%2FDatamining%202020%2D2021%2FPCA%2Fface%5Fdataset&originalPath=aHR0cHM6Ly9lc3R1ZHVzZnFlZHUtbXkuc2hhcmVwb2ludC5jb20vOmY6L2cvcGVyc29uYWwvbnBlcmV6X3VzZnFfZWR1X2VjL0V2ckdGWGRWaTlGTHE5SlZPVVRmYTM4QmpLTGZMZjF3Z3MwSnoxa3lCRFdlT1E_cnRpbWU9Smc0U3JBaWEyRWc