Model Settings in the Data Dictionary
Explains about ALL/USER/DBA_MINING_MODEL_SETTINGS in data
dictionary view.
Information about Oracle Machine Learning model settings can be obtained from the data dictionary view
ALL/USER/DBA_MINING_MODEL_SETTINGS. When used with the
ALL prefix, this view returns information about the settings for the
models accessible to the current user. When used with the USER prefix, it
returns information about the settings for the models in the user's schema. The
DBA prefix is only available for DBAs.
The columns of
ALL_MINING_MODEL_SETTINGS are
described as follows and explained in the following table.
describe all_mining_model_settings
The output is as follows:
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(30)
MODEL_NAME NOT NULL VARCHAR2(30)
SETTING_NAME NOT NULL VARCHAR2(30)
SETTING_VALUE VARCHAR2(4000)
SETTING_TYPE VARCHAR2(7)
Table 6-4 ALL_MINING_MODEL_SETTINGS
| Column | Description |
|---|---|
|
|
Owner of the machine learning model. |
|
|
Name of the machine learning model. |
|
|
Name of the setting. |
|
|
Value of the setting. |
|
|
|
The following query lists the settings for the Support
Vector Machine (SVM) classification model SVMC_SH_CLAS_SAMPLE. The
ALGO_NAME, CLAS_WEIGHTS_TABLE_NAME, and
SVMS_KERNEL_FUNCTION settings are user-specified. These settings have
been specified in a settings table for the model. The SVMC_SH_CLAS_SAMPLE model is created
by the oml4sql-classification-svm.sql example.
Example 6-13 ALL_MINING_MODEL_SETTINGS
COLUMN setting_value FORMAT A35
SELECT setting_name, setting_value, setting_type
FROM all_mining_model_settings
WHERE model_name in 'SVMC_SH_CLAS_SAMPLE';
The output is as follows:
SETTING_NAME SETTING_VALUE SETTING
------------------------------ ----------------------------------- -------
SVMS_ACTIVE_LEARNING SVMS_AL_ENABLE DEFAULT
PREP_AUTO OFF DEFAULT
SVMS_COMPLEXITY_FACTOR 0.244212 DEFAULT
SVMS_KERNEL_FUNCTION SVMS_LINEAR INPUT
CLAS_WEIGHTS_TABLE_NAME svmc_sh_sample_class_wt INPUT
SVMS_CONV_TOLERANCE .001 DEFAULT
ALGO_NAME ALGO_SUPPORT_VECTOR_MACHINES INPUTRelated Topics
ALL_MINING_MODELS
Describes an example of ALL_MINING_MODELS and shows a sample query.
The following example describes ALL_MINING_MODELS and shows a sample query.
Example 6-14 ALL_MINING_MODELS
describe ALL_MINING_MODELS
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
MINING_FUNCTION VARCHAR2(30)
ALGORITHM VARCHAR2(30)
CREATION_DATE NOT NULL DATE
BUILD_DURATION NUMBER
MODEL_SIZE NUMBER
BUILD_SOURCE CLOB
PARTITIONED VARCHAR2(3)
COMMENTS VARCHAR2(4000)The following query returns the models accessible to you that use the Support Vector Machine algorithm.
SELECT mining_function, model_name
FROM all_mining_models
WHERE algorithm = 'SUPPORT_VECTOR_MACHINES'
ORDER BY mining_function, model_name;
The
output is as
follows:
MINING_FUNCTION MODEL_NAME
------------------------- --------------------
CLASSIFICATION PART2_CLAS_SAMPLE
CLASSIFICATION PART_CLAS_SAMPLE
CLASSIFICATION SVMC_SH_CLAS_SAMPLE
CLASSIFICATION SVMO_SH_CLAS_SAMPLE
CLASSIFICATION T_SVM_CLAS_SAMPLE
REGRESSION SVMR_SH_REGR_SAMPLE The models are created by the following examples:
- PART2_CLAS_SAMPLE by
oml4sql-partitioned-models-svm.sql - PART_CLAS_SAMPLE by
oml4sql-partitioned-models-svm.sql - SVMC_SH_CLAS_SAMPLE by
oml4sql-classification-svm.sql - SVMO_SH_CLAS_SAMPLE by
oml4sql-anomaly-detection-1class-svm.sql - T_SVM_CLAS_SAMPLE by
oml4sql-classification-text-mining-svm.sql - SVMR_SH_REGR_SAMPLE by
oml4sql-regression-svm.sql
ALL_MINING_MODEL_ATTRIBUTES
Describes an example of ALL_MINING_MODEL_ATTRIBUTES and shows a sample query.
The following example describes ALL_MINING_MODEL_ATTRIBUTES and shows a sample query. Attributes are the predictors or conditions that are used to create models and score data.
Example 6-15 ALL_MINING_MODEL_ATTRIBUTES
describe ALL_MINING_MODEL_ATTRIBUTES
The output is as follows:
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
ATTRIBUTE_NAME NOT NULL VARCHAR2(128)
ATTRIBUTE_TYPE VARCHAR2(11)
DATA_TYPE VARCHAR2(106)
DATA_LENGTH NUMBER
DATA_PRECISION NUMBER
DATA_SCALE NUMBER
USAGE_TYPE VARCHAR2(8)
TARGET VARCHAR2(3)
ATTRIBUTE_SPEC VARCHAR2(4000)The following query returns the attributes of an SVM classification model named
T_SVM_CLAS_SAMPLE. The model has both categorical and numerical attributes and includes
one attribute that is unstructured text. The model is created by
the oml4sql-classification-text-mining-svm.sql example
SELECT attribute_name, attribute_type, target
FROM all_mining_model_attributes
WHERE model_name = 'T_SVM_CLAS_SAMPLE'
ORDER BY attribute_name;
The output is as follows:
ATTRIBUTE_NAME ATTRIBUTE_TYPE TAR
------------------------- -------------------- ---
AFFINITY_CARD CATEGORICAL YES
AGE NUMERICAL NO
BOOKKEEPING_APPLICATION NUMERICAL NO
BULK_PACK_DISKETTES NUMERICAL NO
COMMENTS TEXT NO
COUNTRY_NAME CATEGORICAL NO
CUST_GENDER CATEGORICAL NO
CUST_INCOME_LEVEL CATEGORICAL NO
CUST_MARITAL_STATUS CATEGORICAL NO
EDUCATION CATEGORICAL NO
FLAT_PANEL_MONITOR NUMERICAL NO
HOME_THEATER_PACKAGE NUMERICAL NO
HOUSEHOLD_SIZE CATEGORICAL NO
OCCUPATION CATEGORICAL NO
OS_DOC_SET_KANJI NUMERICAL NO
PRINTER_SUPPLIES NUMERICAL NO
YRS_RESIDENCE NUMERICAL NO
Y_BOX_GAMES NUMERICAL NOALL_MINING_MODEL_PARTITIONS
Describes an example of ALL_MINING_MODEL_PARTITIONS and shows a sample query.
The following example describes ALL_MINING_MODEL_PARTITIONS and shows a sample query.
Example 6-16 ALL_MINING_MODEL_PARTITIONS
describe ALL_MINING_MODEL_PARTITIONS
The output is as follows:
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
PARTITION_NAME VARCHAR2(128)
POSITION NUMBER
COLUMN_NAME NOT NULL VARCHAR2(128)
COLUMN_VALUE VARCHAR2(4000)
The following query returns the partition names and partition key values for two partitioned models. Model PART2_CLAS_SAMPLE has a two column partition key with system-generated partition names. The models are created by the oml4sql-partitioned-models-svm.sql example.
SELECT model_name, partition_name, position, column_name, column_value
FROM all_mining_model_partitions
ORDER BY model_name, partition_name, position;
The output is as follows:
MODEL_NAME PARTITION_ POSITION COLUMN_NAME COLUMN_VALUE
-------------------- ---------- -------- -------------------- ---------------
PART2_CLAS_SAMPLE DM$$_P0 1 CUST_GENDER F
PART2_CLAS_SAMPLE DM$$_P0 2 CUST_INCOME_LEVEL HIGH
PART2_CLAS_SAMPLE DM$$_P1 1 CUST_GENDER F
PART2_CLAS_SAMPLE DM$$_P1 2 CUST_INCOME_LEVEL LOW
PART2_CLAS_SAMPLE DM$$_P2 1 CUST_GENDER F
PART2_CLAS_SAMPLE DM$$_P2 2 CUST_INCOME_LEVEL MEDIUM
PART2_CLAS_SAMPLE DM$$_P3 1 CUST_GENDER M
PART2_CLAS_SAMPLE DM$$_P3 2 CUST_INCOME_LEVEL HIGH
PART2_CLAS_SAMPLE DM$$_P4 1 CUST_GENDER M
PART2_CLAS_SAMPLE DM$$_P4 2 CUST_INCOME_LEVEL LOW
PART2_CLAS_SAMPLE DM$$_P5 1 CUST_GENDER M
PART2_CLAS_SAMPLE DM$$_P5 2 CUST_INCOME_LEVEL MEDIUM
PART_CLAS_SAMPLE F 1 CUST_GENDER F
PART_CLAS_SAMPLE M 1 CUST_GENDER M
PART_CLAS_SAMPLE U 1 CUST_GENDER U ALL_MINING_MODEL_SETTINGS
Describes an example of ALL_MINING_MODEL_SETTINGS and shows a sample query.
The following example describes ALL_MINING_MODEL_SETTINGS and shows a sample query. Settings influence model behavior. Settings may be specific to an algorithm or to a machine learning technique, or they may be general.
Example 6-17 ALL_MINING_MODEL_SETTINGS
describe ALL_MINING_MODEL_SETTINGS
The output is as follows:
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
SETTING_NAME NOT NULL VARCHAR2(30)
SETTING_VALUE VARCHAR2(4000)
SETTING_TYPE VARCHAR2(7)The following query returns the settings for a model named SVD_SH_SAMPLE. The model uses the Singular Value Decomposition algorithm for feature extraction. The model is created by the oml4sql-singular-value-decomposition.sql example.
SELECT setting_name, setting_value, setting_type
FROM all_mining_model_settings
WHERE model_name = 'SVD_SH_SAMPLE'
ORDER BY setting_name;
The output is as follows:
SETTING_NAME SETTING_VALUE SETTING
------------------------------ ------------------------------ -------
ALGO_NAME ALGO_SINGULAR_VALUE_DECOMP INPUT
ODMS_DETAILS ODMS_ENABLE DEFAULT
ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO DEFAULT
ODMS_SAMPLING ODMS_SAMPLING_DISABLE DEFAULT
PREP_AUTO OFF INPUT
SVDS_SCORING_MODE SVDS_SCORING_SVD DEFAULT
SVDS_U_MATRIX_OUTPUT SVDS_U_MATRIX_ENABLE INPUT ALL_MINING_MODEL_VIEWS
Describes an example of ALL_MINING_MODEL_VIEWS and shows a sample query.
ALL_MINING_MODEL_VIEWS and shows a sample query. Model views provide details on the models.
Example 6-18 ALL_MINING_MODEL_VIEWS
describe ALL_MINING_MODEL_VIEWS
The output is as follows:
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
VIEW_NAME NOT NULL VARCHAR2(128)
VIEW_TYPE VARCHAR2(128)
The following query returns the model views for the SVD_SH_SAMPLE model. The model uses the Singular Value Decomposition algorithm for feature extraction. The model is created by the oml4sql-singular-value-decomposition.sql example.
SELECT view_name, view_type
FROM all_mining_model_views
WHERE model_name = 'SVD_SH_SAMPLE'
ORDER BY view_name;
The output is as follows:
VIEW_NAME VIEW_TYPE
------------------------- --------------------------------------------------
DM$VESVD_SH_SAMPLE Singular Value Decomposition S Matrix
DM$VGSVD_SH_SAMPLE Global Name-Value Pairs
DM$VNSVD_SH_SAMPLE Normalization and Missing Value Handling
DM$VSSVD_SH_SAMPLE Computed Settings
DM$VUSVD_SH_SAMPLE Singular Value Decomposition U Matrix
DM$VVSVD_SH_SAMPLE Singular Value Decomposition V Matrix
DM$VWSVD_SH_SAMPLE Model Build Alerts ALL_MINING_MODEL_XFORMS
Describes an example of ALL_MINING_MODEL_XFORMS and provides a sample query.
ALL_MINING_MODEL_XFORMS and provides a sample query.
Example 6-19 ALL_MINING_MODEL_XFORMS
describe ALL_MINING_MODEL_XFORMS
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER NOT NULL VARCHAR2(128)
MODEL_NAME NOT NULL VARCHAR2(128)
ATTRIBUTE_NAME VARCHAR2(128)
ATTRIBUTE_SUBNAME VARCHAR2(4000)
ATTRIBUTE_SPEC VARCHAR2(4000)
EXPRESSION CLOB
REVERSE VARCHAR2(3)The following query returns the embedded transformations for a model
PART2_CLAS_SAMPLE. The model is created by the
oml4sql-partitioned-models-svm.sql example.
SELECT attribute_name, expression
FROM all_mining_model_xforms
WHERE model_name = 'PART2_CLAS_SAMPLE'
ORDER BY attribute_name;
The output is as follows:
ATTRIBUTE_NAME
-------------------------
EXPRESSION
--------------------------------------------------------------------------------
CUST_INCOME_LEVEL
CASE CUST_INCOME_LEVEL WHEN 'A: Below 30,000' THEN 'LOW'
WHEN 'L: 300,000 and above' THEN 'HIGH'
ELSE 'MEDIUM' END