Dimensionality Reduction

This section presents dimensionality reduction applications, which transform high-dimensional data into a more compact representation while preserving essential information. These methods simplify datasets by removing redundancy and emphasizing the most relevant patterns, making analyses more efficient and interpretable.

• Principal Component Analysis