PCA vs ICA vs Factor Analysis: What Each Actually Captures
Dimensionality reduction is a cornerstone of data science, yet the three most prominent techniques—Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Factor Analysis (FA)—are frequently confused or used interchangeably despite capturing fundamentally different aspects of data structure. Understanding what each method actually extracts from your data determines whether you’ll uncover meaningful patterns or produce … Read more