You can learn a great deal about the Oracle Data Mining API from the data mining sample programs. The programs illustrate typical approaches to data preparation, algorithm selection, algorithm tuning, testing, and scoring.
The programs are easy to use. They include extensive inline comments to help you understand the code. They delete all temporary objects on exit; you can run the programs repeatedly without setup or cleanup.
The data mining sample programs are installed with Oracle Database Examples in the demo directory under Oracle Home. The demo directory contains sample programs that illustrate many features of Oracle Database. You can locate the data mining files by doing a directory listing of dm*.sql. Example A-1 shows this directory listing on a Linux system.
Note that the directory listing in Example A-1 includes one file, dmhpdemo.sql, that is not a data mining program.
The data mining sample programs create a set of mining models in the user's schema. After executing the programs, you can list the models with a query like the one in Example A-2.
Example A-1 Directory Listing of the Data Mining Sample Programs
> cd $ORACLE_HOME/rdbms/demo > ls dm*.sql dmaidemo.sql dmkmdemo.sql dmsvddemo.sql dmardemo.sql dmnbdemo.sql dmsvodem.sql dmdtdemo.sql dmnmdemo.sql dmsvrdem.sql dmdtxvlddemo.sql dmocdemo.sql dmtxtnmf.sql dmemdemo.sql dmsh.sql dmtxtsvm.sql dmglcdem.sql dmshgrants.sql dmglrdem.sql dmstardemo.sql dmhpdemo.sql dmsvcdem.sql
Example A-2 Models Created by the Sample Programs
SELECT mining_function, algorithm, model_name FROM user_mining_models
ORDER BY mining_function;
MINING_FUNCTION ALGORITHM MODEL_NAME
------------------------------ ------------------------------ -------------------
ASSOCIATION_RULES APRIORI_ASSOCIATION_RULES AR_SH_SAMPLE
CLASSIFICATION GENERALIZED_LINEAR_MODEL GLMC_SH_CLAS_SAMPLE
CLASSIFICATION SUPPORT_VECTOR_MACHINES T_SVM_CLAS_SAMPLE
CLASSIFICATION SUPPORT_VECTOR_MACHINES SVMC_SH_CLAS_SAMPLE
CLASSIFICATION SUPPORT_VECTOR_MACHINES SVMO_SH_CLAS_SAMPLE
CLASSIFICATION NAIVE_BAYES NB_SH_CLAS_SAMPLE
CLASSIFICATION DECISION_TREE DT_SH_CLAS_SAMPLE
CLUSTERING EXPECTATION_MAXIMIZATION EM_SH_CLUS_SAMPLE
CLUSTERING O_CLUSTER OC_SH_CLUS_SAMPLE
CLUSTERING KMEANS KM_SH_CLUS_SAMPLE
CLUSTERING KMEANS DM_STAR_CLUSTER
FEATURE_EXTRACTION SINGULAR_VALUE_DECOMP SVD_SH_SAMPLE
FEATURE_EXTRACTION NONNEGATIVE_MATRIX_FACTOR NMF_SH_SAMPLE
FEATURE_EXTRACTION NONNEGATIVE_MATRIX_FACTOR T_NMF_SAMPLE
REGRESSION SUPPORT_VECTOR_MACHINES SVMR_SH_REGR_SAMPLE
REGRESSION GENERALIZED_LINEAR_MODEL GLMR_SH_REGR_SAMPLE