Transformations
Once data is loaded and any necessary preprocessing and feature extraction is done, one of mlpack’s transformations can be used to transform data into a new space.
Note: this section is under construction and not all functionality is documented yet.
🔗 Matrix decompositions
Decompose a matrix into two or more components.
🔗 Linear transformations
Linearly map a matrix onto a new basis, optionally performing dimensionality reduction.
🔗 Metric learning techniques
Learn a distance metric based on a data matrix.
🔗 Coding techniques
Encode data points in a matrix as a combination of points in a dictionary.
- LocalCoordinateCoding: local coordinate coding with dictionary learning
- SparseCoding: sparse coding with dictionary learning