S6E16 Correspondence Analysis
Quantitude
00:00
Understanding Dimensionality Reduction and Data Relationships
This chapter explores principal components analysis and correspondence analysis, focusing on how to reduce dimensionality and interpret chi-square statistics. It discusses the structural distinctions between correlation matrices and correspondence matrices while examining the significance of dependencies through inertia. Additionally, the chapter highlights the decision-making process for selecting dimensions in visualizing data relationships and the challenges of interpreting complex multivariate spaces.
Transcript
Play full episode
