◑ applying · kind algorithm · level 3 · 14.17h
- Requiere: Singular Value Decomposition
- Implementa: Dimensionality Reduction
- Aplica: Feature Engineering
Linear projection onto the directions of maximum variance, computed via the SVD. The default first move for compression and de-noising.
Principal component analysis (PCA) is a linear Dimensionality Reduction technique with applications in exploratory data analysis, visualization and data preprocessing.
Enlaces
- Requiere: Singular Value Decomposition
- Implementa: Dimensionality Reduction
- Aplica: Feature Engineering