Data Mining - Non-Negative Matrix Factorization (NMF) Algorithm

Thomas Bayes


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.

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