How to Build a Data Mining Model with Oracle Database?
You must be wondering whether the Data mining model with Oracle will be created with accuracy or not? The Oracle database combined with all the schema objects will surely clear all your doubts regarding the mining activities. You need to follow the step by step method of creating this particular model.
Step 1: Preparation
This step includes the overall preparation of the data. At first the case table needs to be created. Here the records of the data are generally called as cases. Each of the case does have a unique identification number. The table where all the records are accumulated is specifically called the case table. All the data that needs to be mined should be in a single table or can be viewed at a single platform. Here is an example of a sample case table.
SELECT cust_id, cust_age, cust_gender, cust_phone_number FROM customers WHERE cust_id < 10
Column Data Types: The data mining activities accept some data type in columnar form also. The Enterprise Performance Management (EPM) can also perform with the commands like CHAR, VARCHAR2, FLOAT, NUMBER, and DM_NESTED_NUMERICALS. All the data which are of nested types are all accumulated in the “Nested Data” but except the case ID which is not possible to fit in the columnar types of tables.
Step 2 : Specification Of Settings
As a large number of data settings are available for the purpose of mining, you need to specify your own settings according to the need. The packages of the Oracle database contain different types of settings to choose from. You need to modify the function and the algorithm by setting the characteristics of the global models. The automatic data preparation function needs to be enabled or disabled according to your choice. The table of settings should also be specified with columns containing setting_name, setting_value. After that the cost matrix table needs to be edited as required. If any prior probabilities are present, you need to specify that also. The class weights can be mentioned in the columns with target_value or class_weight whichever is applicable.
Step 3: Creating The Model
The model can be created by using the DBMS data mining packages. It can easily build the data in the case table with the specific model name, function name, the name of the data schema, case ID column name, target column name and also the transform list.
Step 4: Viewing The Model
The details of the models need to be viewed efficiently. You need to acquire the model details with all the algorithms from the existing table. The command can be GET_MODEL_DETAILS or the GET_MODEL_TRANSFORMATIONS. You can easily go through the algorithms of linear models and the decision tree and sometimes the support vector machine.
Mining Model Schema Objects: After the successful vision of the model the data mining can be done from the data dictionary. The models can be selected by their name, build duration, creation date, algorithm or the size of the model.
Step 5: Testing The Model
After the completion of the building process, the model needs to be tested properly. There can be various test metrics available for the data mining concepts. The classification and the regression analysis can be done through these metrics.
Step 6: Evaluation
This is the final step where you can evaluate the model properly. Is the model fully accurate? Is the model able to answer all your business queries? What is the support system of the model?
Therefore you can ensure a proper data mining activity if your model is well built.
Author Bio: Aya Mutt is an Oracle professional who is working on the Enterprise Performance Management (EPM) since 10 years. She is also a passionate blogger who loves writing technical articles in her spare time.