1. Machine Learning for SQL Use Cases
  2. Concepts
  3. Machine Learning Algorithms
  4. About NMF
  5. Tuning the NMF Algorithm

Tuning the NMF Algorithm

Learn about configuring parameters for Non-Negative Matrix Factorization (NMF).

Oracle Machine Learning for SQL supports five configurable parameters for NMF. All of them have default values which are appropriate for most applications of the algorithm. The NMF settings are:

  • Number of features. By default, the number of features is determined by the algorithm.

  • Convergence tolerance. The default is .05.

  • Number of iterations. The default is 50.

  • Random seed. The default is -1.

  • Non-negative scoring. You can specify whether negative numbers must be allowed in scoring results. By default they are allowed.

See Also:

DBMS_DATA_MINING —Algorithm Settings: Non-Negative Matrix Factorization for a listing and explanation of the available model settings.

Note:

The term hyperparameter is also interchangeably used for model setting.