A Unsupervised Feature Extraction algorithm.
Non-Negative Matrix Factorization (NMF):
- generates new attributes using linear combinations of the original attributes.
- Creates new attributes that represent the same information using fewer attributes
The coefficients of the linear combinations are non-negative.
During model apply, an NMF model maps the original data into the new set of attributes (features) discovered by the model.