Principal Component Analysis(PCA)

Principal Component Analysis(PCA)

Principal Component Analysis(PCA) Principal Component Analysis (PCA) is an unsupervised machine learning feature reduction technique for high-dimensional and correlated data sets. Images and text documents have high dimensional data sets which requires unnecessary computation power and storage. Basic goal of PCA is to select features which have high variance. High variance of a feature indicates … Read more Principal Component Analysis(PCA)