Principal Component, Unsupervised Learning, Dimensionality Reduction, Interview Questions, Machine Learning.
orthogonal principal components. Sometimes, data demands non-orthogonal principal components to represent the data. (C) PCA always considers the low variance components in the data as noise and recommends throwing away those components. But, sometimes those components play a major role in a