Model details describe model attributes, rules, statistics, and other information about the model. The DBMS_DATA_MINING
package supports a separate GET_MODEL_DETAILS
function for each algorithm. Global details are also available for Generalized Linear Models, Expectation Maximization, Singular Value Decompostion, and Association Rules.
Model details reverse the transformations applied to the attributes, thus enabling the information to be easily understood by a user. You can obtain the transformations embedded in the model by invoking the DBMS_DATA_MINING.GET_MODEL_TRANSFORMATIONS
function.
The query in Example 5-3 returns the coefficients for several attribute values in a GLM regression model called GLMR_SH_Regr_sample
. Additional details available for this algorithm include: standard error, test statistic, p value, standard coefficient, lower coefficient limit, and upper coefficient limit.
The query in Example 5-4 returns global details for the same model.
Example 5-3 Model Details for GLM Regression
SELECT attribute_name, attribute_value, coefficient FROM TABLE(dbms_data_mining.get_model_details_glm('GLMR_SH_Regr_sample')) WHERE attribute_name IN ('AFFINITY_CARD','BULK_PACK_DISKETTES','COUNTRY_NAME') ORDER BY class, attribute_name, attribute_value; ATTRIBUTE_NAME ATTRIBUTE_VALUE COEFFICIENT -------------------- -------------------- ----------- AFFINITY_CARD -.58234968 BULK_PACK_DISKETTES -.99684665 COUNTRY_NAME Argentina -1.2032688 COUNTRY_NAME Australia .000541598 COUNTRY_NAME Brazil 5.29534224 COUNTRY_NAME Canada 4.02414761 COUNTRY_NAME China .878394982 COUNTRY_NAME Denmark -2.9852215 COUNTRY_NAME France -1.0946872 COUNTRY_NAME Germany -1.6345684 COUNTRY_NAME Italy -1.2749328 COUNTRY_NAME Japan -6.259627 COUNTRY_NAME New Zealand 5.07675762 COUNTRY_NAME Poland 2.20458524 COUNTRY_NAME Saudi Arabia .443146197 COUNTRY_NAME Singapore -4.9472244 COUNTRY_NAME South Africa .493327068 COUNTRY_NAME Spain -3.0895076 COUNTRY_NAME Turkey -5.9014625 COUNTRY_NAME United Kingdom 2.25154714
Example 5-4 Global Details for GLM Regression
SELECT * FROM TABLE(dbms_data_mining.get_model_details_global('GLMR_SH_Regr_sample')) ORDER BY global_detail_name; GLOBAL_DETAIL_NAME GLOBAL_DETAIL_VALUE ------------------------------ ------------------- ADJUSTED_R_SQUARE .732 AIC 5943.057 COEFF_VAR 18.165 CORRECTED_TOTAL_DF 1499.000 CORRECTED_TOT_SS 278740.504 DEPENDENT_MEAN 38.892 ERROR_DF 1420.000 ERROR_MEAN_SQUARE 49.908 ERROR_SUM_SQUARES 70869.218 F_VALUE 52.291 GMSEP 52.722 HOCKING_SP .035 J_P 52.570 MODEL_CONVERGED 1.000 MODEL_DF 79.000 MODEL_F_P_VALUE .000 MODEL_MEAN_SQUARE 2609.739 MODEL_SUM_SQUARES 206169.407 NUM_PARAMS 80.000 NUM_ROWS 1500.000 ROOT_MEAN_SQ 7.065 R_SQ .746 SBIC 6368.114 VALID_COVARIANCE_MATRIX .000