4.7 The CREATE_MODEL Procedure
The CREATE_MODEL
procedure of the
DBMS_DATA_MINING
package uses the specified data to create a machine learning model with the specified name and machine learning
function.
The model can be created with configuration settings and user-specified transformations.
PROCEDURE CREATE_MODEL( model_name IN VARCHAR2, mining_function IN VARCHAR2, data_table_name IN VARCHAR2, case_id_column_name IN VARCHAR2, target_column_name IN VARCHAR2 DEFAULT NULL, settings_table_name IN VARCHAR2 DEFAULT NULL, data_schema_name IN VARCHAR2 DEFAULT NULL, settings_schema_name IN VARCHAR2 DEFAULT NULL, xform_list IN TRANSFORM_LIST DEFAULT NULL);
You can also rename the model using the RENAME_MODEL
procedure of the
DBMS_DATA_MINING
package. The procedure changes the value of the machine
learning model specified against MODEL_NAME
with another name that you
specify.
The following example builds a classification model using the Support Vector Machine algorithm.
Create the settings table CREATE TABLE svm_model_settings ( setting_name VARCHAR2(30), setting_value VARCHAR2(30)); -- Populate the settings table -- Specify SVM. By default, Naive Bayes is used for classification. -- Specify ADP. By default, ADP is not used. BEGIN INSERT INTO svm_model_settings (setting_name, setting_value) VALUES (dbms_data_mining.algo_name, dbms_data_mining.algo_support_vector_machines); INSERT INTO svm_model_settings (setting_name, setting_value) VALUES (dbms_data_mining.prep_auto,dbms_data_mining.prep_auto_on); COMMIT; END; / -- Create the model using the specified settings BEGIN DBMS_DATA_MINING.CREATE_MODEL( model_name => 'svm_model', mining_function => dbms_data_mining.classification, data_table_name => 'mining_data_build_v', case_id_column_name => 'cust_id', target_column_name => 'affinity_card', settings_table_name => 'svm_model_settings'); END; /