Principal Components Analysis in TypeScript (Part 4): Turning PCA Into Interpretable Factor Analysis

About this episode

This episode discusses how to turn PCA into interpretable factor analysis using TypeScript.

This story was originally published on HackerNoon at: https://hackernoon.com/principal-components-analysis-in-typescript-part-4-turning-pca-into-interpretable-factor-analysis . Remember how PCA collapses data with 100 dimensions into a single dimension, wouldn't it be cool if this dimension were interpretable. Factor Analysis does that Check more stories related to data-science at: https://hackernoon.com/c/data-science . You can also check exclusive content about #data-analysis , #typescript , #principal-component-analysis , #factor-analysis , #singular-value-decomposition , #interpretable-ai , #dimensionality-reduction , #exploratory-data-analysis , and more. This story was written by: @bitanath . Learn more about this writer by checking @bitanath's about page, and for more stories, please visit hackernoon.com . Now remember how PCA collapses data with 100 dimensions into a single dimension, wouldn't it be cool if this dimension was interpretable. For example, let's say the 100 columns were like stress, smoking frequency, alcohol ml etc etc.. you see where I am going with this, the final dimension would be something like cardiac arrest or premature demise. On that cheery note…

Topics covered

• Principal Components Analysis
• Factor Analysis
• Data Science
• TypeScript
• Dimensionality Reduction

Keywords

• PCA
• Factor Analysis
• TypeScript
• Dimensionality Reduction
• Interpretable AI
• Exploratory Data Analysis

Mentioned in this episode

Organizations: HackerNoon

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