Data Science, Machine Learning, Unsupervised Learning, Dimensionality Reduction, Cruio.
features (variables) in a dataset while retaining the most relevant information. It is commonly used to address the curse of dimensionality and to simplify the data for visualization, analysis, and modeling. By reducing the dimensionality, we aim to remove noise, redundancy, and irrelevant