Machine Learning Functions

Machine learning functions let you work with your data set in different stages of the data analysis process:

  • Preparing models
  • Training models
  • Evaluating models
  • Applying models
  • Managing models

Some Vertica machine learning functions are implemented as Vertica UDx functions, while others are implemented as meta-functions:

  • A UDx function accepts an input relation name from a FROM clause. The SELECT statement that calls the functions is composable—it can be used as a sub-query in another SELECT statement.
  • A meta-function accepts the input relation name as a single-quoted string passed to it as an argument or a named parameter. The data that the SELECT statement returns cannot be used in a sub-query. Machine learning meta-functions do not support temporary tables.

All machine learning functions automatically cast NUMERIC arguments to FLOAT.

Before using a machine learning function, be aware that any open transaction on the current session might be committed.

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