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;
/