Chapter 16 Dimensionality reduction
Learning objectives:
- Understand recipes
- Create, prep, and bake recipes outside of a workflow to test or debug the recipes.
- Understand dimensionality reduction techniques
- Compare and contrast four dimensionality reduction techniques (techniques used to create a small set of features that capture the main aspects of the original predictor set):
- Principal component analysis (PCA)
- Partial least squares (PLS)
- Independent component analysis (ICA)
- Uniform manifold approximation and projection (UMAP)
- Use dimensionality reduction techniques in conjunction with modeling techniques.
- Compare and contrast four dimensionality reduction techniques (techniques used to create a small set of features that capture the main aspects of the original predictor set):