Mini toolsDefinition
Methods for breaking down matrices into simpler components, crucial for dimensionality reduction and data analysis.
Detailed Explanation
Matrix decomposition techniques break down complex matrices into simpler, more manageable components. It includes methods like SVD, eigendecomposition, and LU decomposition. These are essential for data compression, dimensionality reduction, and solving linear systems.
Use Cases
Principal Component Analysis, data compression, feature extraction
