5 Scoring and Deployment

Explains the scoring and deployment features of Oracle Machine Learning for SQL.

• About Scoring and Deployment
  Scoring is the application of models to new data. In Oracle Machine Learning for SQL, scoring is performed by SQL language functions.
• Use the Oracle Machine Learning for SQL Functions
  Some of the benefits of using SQL functions for Oracle Machine Learning for SQL are listed.
• Prediction Details
  Prediction details are XML strings that provide information about the score.
• Real-Time Scoring
  You can perform real-time scoring by running a SQL query. An example shows a real-time query using PREDICTION_PROBABILITY function. Based on the result, a customer representative can offer a value card to the customer.
• Dynamic Scoring
  You can perform dynamic scoring if, for some reason, you do not want to apply a predefined model.
• Cost-Sensitive Decision Making
  Costs are user-specified numbers that bias classification. The algorithm uses positive numbers to penalize more expensive outcomes over less expensive outcomes. Higher numbers indicate higher costs.
• DBMS_DATA_MINING.APPLY
  The APPLY procedure in DBMS_DATA_MINING is a batch apply operation that writes the results of scoring directly to a table.