About Model Settings

4.2 About Model Settings

You can specify settings that affect the characteristics of a model.

Some settings are general, some are specific to an Oracle Machine Learning function, and some are specific to an algorithm.

All settings have default values. If you want to override one or more of the settings for a model, then you must specify the settings with the **params parameter when instantiating the model or later by using the set_params method of the model.

If a parameter is specified by both OML4R algorithm parameters and odm.settings, the value in odm.settings is used.

Example 4-1 Specifying Model Settings

This example shows the creation of an Expectation Maximization (EM) model and the changing of a setting.

settings = list(
 EMCS_NUM_ITERATIONS= 20,
 EMCS_RANDOM_SEED= 7)
EM.MOD <- ore.odmEM(~.-CUST_ID, CUST_DF, num.centers = 3, odm.settings = 
settings)

Parent topic: Reference