Principal Component Analysis (PCA) is a process to achieve Dimensionality Reduction which means reducing the number of features or dimensions while retaining the original variance of the whole data set. The new set of principal components have the variance in descending order so that the first component has maximum variance. Data: We will use the same Breast Cancer data we have used in Support Vector Machines […]