Unsupervised Learning Dimensionality Reduction – Feature Elimination vs Extraction
Feature Elimination and Feature Extraction are two common techniques used in dimensionality reduction, a process aimed at reducing the number of features (or dimensions) in a dataset while preserving the most important information. Both techniques are used to address the curse of dimensionality, improve computational efficiency, and potentially enhance model performance. However, they differ in…