Pattern Recognition using PCA: Variables and their Geometric Relationships

Principal component analysis is a commonly used technique in multi-variate statistics and pattern recognition literature. In this post I try to merge ideas of Geometric and Algebraic interpretation of data as vectors in a vector space and its relationship with PCA. The 3 major sources used in this blog are: [1] Thomas D. Wickens (1995). The … Continue reading Pattern Recognition using PCA: Variables and their Geometric Relationships